Publications

Cecilia O. Alm, Reynold Bailey, and Hannah Miller. 2022. Remote early research experiences for undergraduate students in computing. In Proceedings of the SIGCSE Technical Symposium 2022, 43-49, Providence, Rhode Island.

Trent Rabe, Anisa Callis, Zhi Zheng, Jamison Heard, Reynold Bailey, and Cecilia O. Alm. Forthcoming. Theory of mind assessment with human-human and human-robot interactions. Accepted to appear in HCII 2022, online.

Nikhil Kaushik, Reynold Bailey, Alexander Ororbia and Cecilia O. Alm. 2021. Eliciting confusion in online conversational tasks. In Proceedings of the 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (at ACII 2021), 1-5, Nara, Japan (online). doi: 10.1109/ACIIW52867.2021.9666351.

Subhra Tewari, Renos Zabounidis, Ammina Kothari, Reynold Bailey, and Cecilia O. Alm. 2021. Perceptions of human and machine-generated articles. Journal of Digital Threats: Research and Practice, 2(2): 1-16.

Cecilia O. Alm and Reynold Bailey. 2021. Transitioning from teaching to mentoring: Supporting students to adopt mentee roles. Journal for STEM Education Research, 4(1), 95-114. doi:10.1007/s41979-020-00045-9.

Saad Hassan, Matt Huenerfauth, and Cecilia O. Alm. 2021. Unpacking the interdependent systems of discrimination: Ableist bias in NLP systems through an intersectional lens. Findings of the Association for Computational Linguistics: EMNLP 2021, 3116-3123, Punta Cana, Dominican Republic.

Farhad Akhbardeh, Cecilia O. Alm, Marcos Zampieri, and Travis Desell. 2021. Handling extreme class imbalance in technical logbook datasets. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Long Papers), pages 4034-4045, online.

Cecilia O. Alm and Alex Hedges. 2021. Visualizing NLP in undergraduate students’ learning about natural language. In Proceedings of the AAAI Conference on Artificial Intelligence, 35(17), pages 15480-15488, EAAI-21, online.

Cecilia O. Alm and Reynold Bailey. 2021. REU mentoring engagement: Contrasting perceptions of administrators and faculty. Proceedings of the 52nd ACM Technical Symposium on Computer Science Education, page 1257, online. Poster.

 

View more publications by Cecilia

Cecilia Ovesdotter Alm, Reynold Bailey, and Hannah Miller, “Remote early research experiences for undergraduate students in computing”, Proceedings of the SIGCSE 2022 Technical Symposium, to appear.

Trent Rabe, Anisa Callis, Zhi Zheng, Jamison Heard, Reynold Bailey, and Cecilia Alm, “Theory of Mind Assessment with Human-Human and Human-Robot Interactions", Proceedings of HCI International 2022, to appear.

Rakshit Kothari, Aayush Chaudhary, Reynold Bailey, Jeff Pelz, Gabriel Diaz, “Ellseg: An Ellipse Segmentation Framework for Robust Gaze Tracking”, IEEE Transactions on Visualization and Computer Graphics (TVCG) - special issue on IEEE Virtual Reality and 3D User Interfaces, Vol. 27, No. 5, pp. 2757-2767, 2021.

Subhra Tewari, Renos Zabounidis, Ammina Kothari, Reynold Bailey, and Cecilia Ovesdotter Alm, “Perceptions of human and machine-generated articles”, Journal of Digital Threats: Research and Practice (DTRAP), Vol. 2, No. 2, Ar. 12, pp. 1-16, 2021.

Cecilia Ovesdotter Alm and Reynold Bailey, “Transitioning from teaching to mentoring: Supporting students to adopt mentee roles”, Journal for STEM Education Research, Vol. 4, No. 1, pp. 95-114, 2021.

Nikhil Kaushik, Reynold Bailey, Alexander Ororbia, and Cecilia Ovesdotter Alm, “Eliciting Confusion in Online Conversational Tasks”, Proceedings of the International Conference on Affective Computing & Intelligent Interaction ACII – Fifth International Workshop on Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction, 2021.

Cecilia Ovesdotter Alm and Reynold Bailey, “REU mentoring engagement: Contrasting perceptions of administrators and faculty”, Proceedings of the 52nd ACM Technical Symposium on Computer Science Education, pp. 1257, 2021.

View more publications by Reynold

Farhad Akhbardeh, Cecilia Ovesdotter Alm, Marcos Zampieri and Travis Desell. Handling Extreme Class Imbalance in Technical Logbook Datasets. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021). Bangkok, Thailand. August 2-4, 2021.

Zimeng Lyu, Shuchita Patwardhan, David Stadem, James Langfeld, Steve Benson, and Travis Desell. Neuroevolution of Recurrent Neural Networks for Time Series Forecasting of Coal-Fired Power Plant Data. ACM Workshop on NeuroEvolution@Work (NEWK@Work}, held in conjunction with ACM Genetic and Evolutionary Computation Conference (GECCO). Lille, France. July 10-14, 2021.

Joshua Karns and Travis Desell. Improving the Scalability of Distributed Neuroevolution Using Modular Congruence Class Generated Innovation Numbers. The 1st Workshop on Evolutionary Algorithms and High Performance Computing (EAHPC), held in conjunction with ACM Genetic and Evolutionary Computation Conference (GECCO). Lille, France. July 10-14, 2021.

AbdElRahman ElSaid, Joshua Karns, Zimeng Lyu, Alexander Ororbia and Travis Desell. Continuous Ant-Based Neural Topology Search. The 24th International Conference on the Applications of Evolutionary Computation (EvoStar: EvoApps 2021). Online. April 7-9, 2021.

Zimeng Lyu, AbdElRahman ElSaid, Joshua Karns, Mohamed Mkaouer and Travis Desell. An Experimental Study of Weight Initialization and Lamarckian Inheritance on Neuroevolution. The 24th International Conference on the Applications of Evolutionary Computation (EvoStar: EvoApps 2021). Online. April 7-9, 2021.

Zimeng Lyu, AbdElRahman ElSaid, Joshua Karns, Mohamed Mkaouer and Travis Desell. Improving Distributed Neuroevolution Using Island Extinction and Repopulation. The 24th International Conference on the Applications of Evolutionary Computation (EvoStar: EvoApps 2021). Online. April 7-9, 2021.

View more publications by Travis

Publication:
Prakash Baskaran, Jamison Heard, and Julie A. Adams. Emergency Clinical Detection via
Wearable Sensors. In Press for Conference for the Human Factors and Ergonomics Society, 2021.

Patent:
Fabbri, Daniel, Joseph Coco, Cheng Ye, Deirdre Scully, Candace McNaughton, Jesse Ehrenfeld,
Christopher Simpson, Laurie Novak, Sean Bloos, Robert Bodenheimer, Richard Paris, Julie A. Adams, and Jamison Heard. “Automatic Sensing for Clinical Decision Support.” U.S. Patent Application 17/203,204, filed September 16, 2021.

View more publications by Jamison

R. S. Gulia, S. A. Mamun, A. Vashist, A. Ganguly, C. Hochgraf, A. Kwasinski, M. Kuhl (2022)  “Evaluation of Wireless Connectivity in an Automated Warehouse at 60 GHz,” Proceedings - 2022 IEEE International Conference on Consumer Electronics (ICCE).

A. Vashist, M.-P. Li, A. Ganguly, C. Hochgraf, R. Ptucha, A. Kwasinski, M. E. Kuhl. “KF-Loc: A Kalman Filter and Machine Learning Integrated Localization System Using Consumer-Grade Millimeter-wave Hardware.” IEEE Consumer Electronics Magazine, doi: 10.1109/MCE.2021.3101060.

View more publications by Clark

Sushant Kafle, Becca Dingman, Matt Huenerfauth. 2021. “Deaf and Hard-of-Hearing Users Evaluating Designs for Highlighting Key Words in Educational Lecture Videos.” ACM Transactions on Accessible Computing, 14, 4, Article 20 (December 2021), 24 pages. DOI: https://doi.org/10.1145/3470651

Saad Hassan, Oliver Alonzo, Abraham Glasser, and Matt Huenerfauth. 2021. “Effect of Sign-recognition Performance on the Usability of Sign-language Dictionary Search.” ACM Transactions on Accessible Computing, 14, 4, Article 18 (December 2021), 33 pages. DOI: https://doi.org/10.1145/3470650

Danielle Bragg, Naomi Caselli, Julie A. Hochgesang, Matt Huenerfauth, Leah Katz-Hernandez, Oscar Koller, Raja Kushalnagar, Christian Vogler, Richard E. Ladner. 2021. “The FATE Landscape of Sign Language AI Datasets: An Interdisciplinary Perspective.” ACM Transactions on Accessible Computing, 14, 2, Article 7 (July 2021), 45 pages. DOI: https://doi.org/10.1145/3436996

Akhter Al Amin, Abraham Glasser, Raja Kushalnagar, Christian Vogler, Matt Huenerfauth. 2021. “Preferences of Deaf or Hard of Hearing Users for Live-TV Caption Appearance.” In: Antona M., Stephanidis C. (eds) Universal Access in Human-Computer Interaction. Access to Media, Learning and Assistive Environments. HCII 2021. Lecture Notes in Computer Science, vol 12769. Springer, Cham. https://doi.org/10.1007/978-3-030-78095-1_15

Akhter Al Amin, Saad Hassan, Matt Huenerfauth. 2021. “Effect of Occlusion on Deaf and Hard of Hearing Users’ Perception of Captioned Video Quality.” In: Antona M., Stephanidis C. (eds) Universal Access in Human-Computer Interaction. Access to Media, Learning and Assistive Environments. HCII 2021. Lecture Notes in Computer Science, vol 12769. Springer, Cham. https://doi.org/10.1007/978-3-030-78095-1_16

Saad Hassan, Matt Huenerfauth, Cecilia Ovesdotter Alm. 2021. “Unpacking the Interdependent Systems of Discrimination: Ableist Bias in NLP Systems through an Intersectional Lens.” In Findings of the Association for Computational Linguistics: EMNLP 2021, Punta Cana, Dominican Republic, November 2021. Pages 3116-3123. Association for Computational Linguistics. https://aclanthology.org/2021.findings-emnlp.267 [34.9% aggregate acceptance rate for EMNLP and Findings of EMNLP]

Sooyeon Lee, Abraham Glasser, Becca Dingman, Zhaoyang Xia, Dimitris Metaxas, Carol Neidle, Matt Huenerfauth. 2021. “American Sign Language Video Anonymization to Support Online Participation of Deaf and Hard of Hearing Users.” In The 23rd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS'21). Association for Computing Machinery, New York, NY, USA, Article 22, 1–13. DOI: https://doi.org/10.1145/3441852.3471200. [29% paper acceptance rate]
Conference Award: Best Paper Nominee, ASSETS 2021. (Top 7% of submissions were nominees.)

Sedeeq Al-khazraji, Becca Dingman, Sooyeon Lee, Matt Huenerfauth. 2021. “At a Different Pace: Evaluating Whether Users Prefer Timing Parameters in American Sign Language Animations to Differ from Human Signers’ Timing.” In The 23rd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS'21). Association for Computing Machinery, New York, NY, USA, Article 40, 1–12. DOI: https://doi.org/10.1145/3441852.3471214 [29% paper acceptance rate]

Oliver Alonzo, Jessica Trussell, Becca Dingman, Matt Huenerfauth. 2021. “Comparison of Methods for Evaluating Complexity of Simplified Texts among Deaf and Hard-of-Hearing Adults at Different Literacy Levels.” In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (CHI ’21). Association for Computing Machinery, New York, NY, USA, Article 279, 1–12. DOI: https://doi.org/10.1145/3411764.3445038 [23% paper acceptance rate]

Vaishnavi Mande, Abraham Glasser, Becca Dingman, Matt Huenerfauth. 2021. “Deaf Users' Preferences Among Wake-Up Approaches during Sign-Language Interaction with Personal Assistant Devices.”  In Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery (CHI’21), New York, NY, USA, Article 370, 1–6. DOI: https://doi.org/10.1145/3411763.3451592 [27% paper acceptance rate]

Abraham Glasser, Vaishnavi Mande, Matt Huenerfauth. 2021. “Understanding Deaf and Hard-of-Hearing Users’ Interest in Sign-Language Interaction with Personal-Assistant Devices.” In Proceedings of the 18th International Web for All Conference - Accessibility and Crisis (W4A’21). ACM, New York, NY, USA. DOI: https://doi.org/10.1145/3430263.3452428 [53% paper acceptance rate]

Akhter Al Amin, Saad Hassan, Matt Huenerfauth. 2021. “Caption-Occlusion Severity Judgments across Live-Television Genres from Deaf and Hard-of-Hearing Viewers.” In Proceedings of the 18th International Web for All Conference - Accessibility and Crisis (W4A’21). ACM, New York, NY, USA. DOI: https://doi.org/10.1145/3430263.3452429  [53% paper acceptance rate]

Matthew Seita, Sarah Andrew, Matt Huenerfauth. 2021. “Deaf and Hard-of-Hearing Users’ Preferences for Hearing Speakers’ Behavior during Technology-Mediated In-Person and Remote Conversations.” In Proceedings of the 18th International Web for All Conference - Accessibility and Crisis (W4A’21). ACM, New York, NY, USA. DOI: https://doi.org/10.1145/3430263.3452429  [53% paper acceptance rate]

Matt Huenerfauth. 2021. “Human-Computer Interaction and Automatic Text Simplification: Understanding the Perspective of Deaf and Hard of Hearing Users.” In: Saggion, H., Štajner, S. and Ferrés, D. (Eds). Proceedings of the First Workshop on Current Trends in Text Simplification (CTTS 2021), co-located with SEPLN 2021. Spanish Society for Natural Language Processing. September 21st, 2021 (Online). http://ceur-ws.org/Vol-2944/abstract1.pdf

Akhter Al Amin, Matt Huenerfauth. 2021. “Perspectives of Deaf and Hard-of-Hearing Viewers on Live-TV Caption Quality.”  In iConference 2021: Diversity, Divergence, Dialogue.  Poster Presentation.
Conference Award: Finalist for Best Poster Award, iConference 2021.

View more publications by Matt

Gallardo, J., Hayes, T.L., Kanan, C. (2021) Self-Supervised Training Enhances Online Continual Learning. In: British Machine Vision Conference (BMVC). [36% accept rate]

Acharya, M., Kanan, C. (2021) 2nd Place Solution for SODA10M Challenge 2021 – Continual Detection Track. In: ICCV 2021 Workshop: Self-supervised Learning for Next-Generation Industry-level Autonomous Driving. [Placed 2nd in competition]

Hayes, T.L., Krishnan, G.P., Bazhenov, M., Siegelmann, H.T., Sejnowski, T.J., Kanan, C. (2021) Replay in deep learning: Current approaches and missing biological elements. Neural Computation. doi:10.1162/neco_a_01433

Mahmood, U., Shrestha, R., Bates, D., Mannelli, L., Corrias, G., Erdi, Y., Kanan, C. (2021) Detecting Spurious Correlations with Sanity Tests for Artificial Intelligence Guided Radiology Systems. Frontiers in Digital Health. doi:10.3389/fdgth.2021.671015

Mahmood, U., Apte, A., Kanan, C., Bates, D., Corrias, G., Manneli, L., Oh, J., Erdi, Y., Nguyen, J., Deasy, J., Shukla-Dave, A. (2021) Quality control of radiomic features using 3D printed CT phantoms. Journal of Medical Imaging. 8(3), 033505. doi: 10.1117/1.JMI.8.3.033505.

Khanal, B., Kanan, C. (2021) How does heterogeneous label noise impact generalization in neural networks? International Symposium on Visual Computing (ISVC).

Hayes, T., Kanan, C. (2021) Selective Replay Enhances Learning in Online Continual Analogical Reasoning. CVPR Workshop on Continual Learning in Computer Vision (CLVISION). [Oral]

Lomonaco, V., Pellegrini, L., Cossu, A., Carta, A., Graffieti, G., Hayes, T., De Lange, M., Masana, M., Pomponi, J., Ven, G., Mundt, M., She, Q., Cooper, K., Forest, J., Belouadah, E., Calderara, S., Parisi, G., Cuzzolin, F., Tolias, A., Scardapane, S., Antiga, L., Ahmad, S., Popescu, A., Kanan, C., Weijer, J., Tuytelaars, T., Bacciu, D., Maltoni, D. (2021) Avalanche: An End-to-End Library for Continual Learning. CVPR Workshop on Continual Learning in Computer Vision (CLVISION). [W&B Best Library Award Winner]

 

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Wentao Bao, Qi Yu, and Yu Kong. OpenTAL: Towards Open Set Temporal Action Localization. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.

Junwen Chen, Gaurav Mittal, Ye Yu, Yu Kong, and Mei Chen. GateHUB: Gated History Unit with Background Suppression for Online Action Detection. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.

Krishna Prasad Neupane, Ervine Zheng, Yu Kong, and Qi Yu. A Dynamic Meta-Learning Model for Time-Sensitive Cold-Start Recommendations. AAAI Conference on Artificial Intelligence (AAAI), 2022.

Xinmiao Lin, Wentao Bao, Matthew Wright, and Yu Kong. Gradient Frequency Modulation for Visually Explaining Video Understanding Models. British Machine Vision Conference (BMVC), 2021.

Wentao Bao, Qi Yu, and Yu Kong. Evidential Deep Learning for Open Set Action Recognition. International Conference on Computer Vision (ICCV), 2021. Oral

Wentao Bao, Qi Yu, and Yu Kong. DRIVE: Deep Reinforced Accident Anticipation with Visual Explanation. International Conference on Computer Vision (ICCV), 2021.

Junwen Chen and Yu Kong. Explainable Video Entailment with Grounded Visual Evidence. International Conference on Computer Vision (ICCV), 2021.

View more publications by Yu

Rahul Singh Gulia, Sayed Ashraf Mamun, Abhishek Vashist, Amlan Ganguly, Clark Hochgraf, Andres Kwasinski, and Michael E Kuhl. “Evaluation of Wireless Connectivity in an Automated Warehouse at 60 GHz,” 2022 IEEE International Conference on Consumer Electronics (ICCE), 1-6, 2022.

Abhishek Vashist, Maojia Patrick Li, Amlan Ganguly, Clark Hochgraf, Raymond Ptucha, Andres Kwasinski, and Michael E Kuhl.  "KF-Loc: A Kalman Filter and Machine Learning Integrated Localization System Using Consumer-Grade Millimeter-wave Hardware," in IEEE Consumer Electronics Magazine, 2021. doi: 10.1109/MCE.2021.3101060.

Bruce Hartpence and Andres Kwasinski. "CNN and MLP neural network ensembles for packet classification and adversary defense." Intelligent and Converged Networks 2.1 (2021): 66-82, 2021.

D.-T. Do, M. -S. Van Nguyen, M. Voznak, A. Kwasinski and J. N. de Souza, "Performance Analysis of Clustering Car-Following V2X System with Wireless Power Transfer and Massive Connections," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2021.3070744, 2021.

Sayed Ashraf Mamun, Amlan Ganguly, Panos P Markopoulos, Minseo K Kwon, and Andres Kwasinski. “NASCon: Network-Aware Server Consolidation for server-centric wireless datacenters.” Sustainable Computing: Informatics and Systems 29, 100452, 2021.

Fatemeh Shah-Mohammadi, Hatem Hussein Enaami, and Andres Kwasinski. "Neural network cognitive engine for autonomous and distributed underlay dynamic spectrum access." IEEE Open Journal of the Communications Society 2, 719-737, 2021.

Patent:
Andres Kwasinski and Fatemeh Shah Mohammadi. "Radio spectrum sharing leveraging link adaptation in primary network." U.S. Patent No. 11,032,826. 8 Jun. 2021.

View more publications by Andres

Cheng, Z., Liang, J., Choi, H., Tao, G., Cao, Z., Liu, D. and Zhang, X., 2022. Physical Attack on Monocular Depth Estimation with Optimal Adversarial PatchesECCV 2022.

Cao, Z., Liu, D. and Chen, Y., 2022. Towards Unbiased Label Distribution Learning for Facial Pose Estimation Using Anisotropic Spherical GaussianECCV 2022.

Yan, L., Ma, S., Wang, Q., Chen, Y., Zhang, X., Savakis, A. and Liu, D., 2022. Video Captioning Using Global-Local RepresentationIEEE Transactions on Circuits and Systems for Video Technology.

Yan, L., Wang, Q., Cui, Y., Feng, F., Quan, X., Zhang, X. and Liu, D., 2022. GL-RG: Global-Local Representation Granularity for Video CaptioningIJCAI 2022.

Wang, Q., Fang, Y., Ravula, A., Feng, F., Quan, X. and Liu, D., 2022, April. WebFormer: The Web-page Transformer for Structure Information Extraction. In Proceedings of the ACM Web Conference 2022 (pp. 3124-3133).

Eduardo Lima (PhD advisee), Xumin Liu: A Structure Alignment Deep Graph Model for Mashup Recommendation. International Conference on Service Oriented Computing (ICSOC: CORE A conference), 2021: 682-690 (Short paper)

Dingrong Wang, Hitesh Sapkota, Xumin Liu, Qi Yu: Deep Reinforced Attention Regression for Partial Sketch Image Retrieval, International Conference on Data Mining (ICDM: CORE A* conference), 2021. (Regular research paper)

Xumin Liu, Erik Golen, Rajendra Raj: DSLP: A Web-based Data Science Learning Platform to Support DS Education for Non-Computing Majors, ACM Special Interest Group on Computer Science Education Conference (SIGCSE: CORE A conference), 2021, Demo track.

Xumin Liu, Erik Golen, Rajendra Raj: Introducing Data Science Topics to Non-Computing Majors, ACM Special Interest Group on Computer Science Education Conference (SIGCSE: CORE A conference), 2021, Workshop track.

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Publications:
R. Yeh, and A. Loui, “Synthesizing and manipulating natural videos using image-to-image translation,” Proceedings IEEE Western NY Image & Signal Processing Workshop, Rochester NY, Oct. 2021.

Abhishek Vashist, Maojia Patrick Li, Amlan Ganguly, Clark Hochgraf, Raymond Ptucha, Andres Kwasinski, Michael E Kuhl. “KF-Loc: A Kalman Filter and Machine Learning Integrated Localization System Using Consumer-Grade Millimeter-wave Hardware.” IEEE Consumer Electronics Magazine, doi: 10.1109/MCE.2021.3101060.

Patents:
Raymond William Ptucha, Alexander C. Loui, Mark D. Wood, David K. Rhoda, David Kloosterman, and Joseph Anthony Manico. "Imaging workflow using facial and non-facial features." U.S. Patent 11,182,590, issued November 23, 2021.

Chi Zhang, Raymond Ptucha, Alexander Loui, and Carl Salvaggio. "System and method for batch-normalized recurrent highway networks." U.S. Patent Application 17/126,745, filed April 8, 2021.

View more publications by Alexander

Yawen Lu, Yuxing Wang, Devarth Parikh, Awais, Khan, Guoyu Lu, Simultaneous Direct Depth Estimation and Synthesis Stereo for Single Image Plant Root Reconstruction, IEEE Transactions on Imaging Processing, 2021

Yawen Lu, Guoyu Lu, SuperThermal: Matching Thermal As Visible Through Thermal Feature Exploration, IEEE Robotics and Automation Letters, 2021

Yawen Lu, Guoyu Lu, Self-supervised Single-image Depth Estimation From Focus and Defocus Clues, IEEE Robotics and Automation Letters, 2021

Zhihua Xie, Jieyi Niu, Yi Li, Guoyu Lu, Regularization and Attention Feature Distillation base on Light CNN for Hyperspectral Face Recognition, Journal of Multimedia Tools and Applications, 2021

Yawen Lu, Guoyu Lu, Bridging the Invisible and Visible World: Translation between RGB and IR Images through Contour Cycle GAN, The 17th IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS), 2021

Yuxing Wang, Yawen Lu, Zhihua Xie, Guoyu Lu, Deep Unsupervised 3D SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment, ACM Multimedia (MM) (oral), 2021

Yawen Lu, Nikola Kasabov and Guoyu Lu, Multi-view Geometry Consistency Network for Facial Micro-Expression Recognition From Various Perspectives, IJCNN 2021

Hao Wang, Tao Zhang, Guoyu Lu, Unsupervised HDR Image Reconstruction Based on Over/Under-Exposed LDR Image Pair, ICME 2021

Yawen Lu, Yuhao Zhu, Guoyu Lu, 3D SceneFlowNet: Self-supervised 3D Scene Flow Estimation based on Graph CNN, ICIP 2021

Zhelin Yu, Lidong Zhu, Guoyu Lu, VINS-Motion: Tightly-coupled Fusion of VINS and Motion Constraint, ICRA 2021

Yuxing Wang, Yawen Lu, Guoyu Lu, Stereo Rectification Based on Epipolar Constrained Neural Network, ICASSP 2021

Bhavesh Deshpande, Sourabh Hanamsheth, Yawen Lu, Guoyu Lu, Matching As Color Images: Thermal Image Local Feature Detection And Description, ICASSP 2021

Yawen Lu, Guoyu Lu, An Alternative of LIDAR in Nighttime: Unsupervised Depth Estimation Based on Single Thermal Image, IEEE Winter Conference on Applications of Computer Vision (WACV) 2021

Yawen Lu, Yuxing Wang, Di Wu, Yuan Xin, Guoyu Lu, Unsupervised Gaze: Exploration of Geometric Constraints for 3D Gaze Estimation, International Conference on Multimedia Modeling (MMM), 2021

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Book Chapter:

D. G. Chachlakis, M. Dhanaraj, P. P. Markopoulos, A. Prater-Bennette, and I. Tomeo, "D-L1-Tucker: Dynamic and Robust Analysis of Tensor Data Based on Absolute Projection Maximization," to appear in Handbook on Dynamic Data Driven Application Systems (Vol. II).

Journal Papers:

S. Colonnese, P. P. Markopoulos, G. Scarano, and D. A. Pados, "FFT Calculation of the L1-norm Principal Component of a Data Matrix," Signal Processing (Elsevier), vol. 189, no. 108286, August 2021.

D. G. Chachlakis, T. Zhou, F. Ahmad, P. P. Markopoulos, "Minimum Mean-Squared Error Autocorrelation Processing in Coprime Arrays," Digital Signal Processing (Elsevier), vol. 114, no. 103034, July 2021.

D. G. Chachlakis, M. Dhanaraj, A. Prater-Bennette, P. P. Markopoulos, "Dynamic L1-norm Tucker Tensor Decomposition,"  IEEE Journal on Selected Topics in Signal Processing, Special Issue on Tensor Decomposition for Signal Processing and Machine Learning, vol. 15, no. 3, pp. 587-602, April 2021.

D. G. Chachlakis and P. P. Markopoulos, " Structured Autocorrelation Matrix Estimation for Coprime Arrays," Signal Processing (Elsevier), vol. 183, no. 107987, June 2021.

Conference Papers:    

M. Sharma, P. P. Markopoulos, E. Saber, M. S. Asif, and A. Prater-Bennette, "Convolutional Auto-Encoder with Tensor-Train Factorization," accepted to appear in Proc. International Conference on Computer Vision, (ICCV 2021), RLS-CV workshop.

M. Mozaffari, P. P. Markopoulos, and A. Prater-Bennette, "Improved L1-Tucker via L1-Fitting," to appear in Proc. European Signal Processing Conference (EUSIPCO 2021), Dublin, Ireland, August 2021.

M. Mozaffari and P. P. Markopoulos, "Robust Barron-Loss Tucker Tensor Decomposition," to appear in Proc. IEEE Asilomar Conference on Signals, Systems, and Computing (IEEE ACSSC), Pacific Grove, CA, November 2021.

M. Sharma, P. P. Markopoulos, and E. Saber, "YOLOrs-LITE: A Lightweight CNN for Real-time Object Detection in Remote Sensing," to appear in Proc. IEEE International Geoscience and Remote Sensing Symposium (IEEE IGARSS), Brussels, Belgium, July 2021.

D. G. Chachlakis and P. P. Markopoulos, Novel Algorithms for Lp-quasi-norm Principal-Component Analysis,” Proc. European Signal Processing Conference (EUSIPCO 2020), Amsterdam, Netherlands, January 2021.

 

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E. Casamassima, A. Herbert, C. Merkel, “Exploring CNN features in the context of adversarial robustness and human perception,” SPIE Applications of Machine Learning, 1184313, 2021.

T. Li and C. Merkel, “Model Extraction and Adversarial Attacks on Neural Networks using Switching Power Information”  International Conference on Artificial Neural Networks (ICANN), 2021.

M. Gorsline, J. Smith, and C. Merkel, “On the Adversarial Robustness of Quantized Neural Networks,” In Proceedings of the 2021 on Great Lakes Symposium on VLSI (GLSVLSI), pp. 189-194, 2021.

View more publications by Cory

Ananthanarayana, Tejaswini, Nikunj Kotecha, Priyanshu Srivastava, Lipisha Chaudhary, Nicholas Wilkins, and Ifeoma Nwogu. "Dynamic Cross-Feature Fusion for American Sign Language Translation." In 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021), pp. 1-8. IEEE, 2021.

Wang, Renke, Yeo Jin Amy Ahn, Daniel Messinger, and Ifeoma Nwogu. "Towards the Synthesis of Parent-Infant Facial Interactions." In 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021), pp. 1-8. IEEE, 2021.

Sharma, Srijan, Kantha Girish Gangadhara, Fei Xu, Anne Solbu Slowe, Mark G. Frank, and Ifeoma Nwogu. "Coupled Systems for Modeling Rapport Between Interlocutors." In 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021), pp. 1-8. IEEE, 2021.

   

Tejaswini Ananthanarayana, Priyanshu Srivastava, Akash Chintha, Akhil Santha, Brian Landy, Joseph Panaro, Andre Webster, Nikunj Kotecha, Shagan Sah, Thomastine Sarchet, Raymond Ptucha, and Ifeoma Nwogu. “Deep learning methods for sign language translation.” In ACM Transactions on Accessible Computing (TACCESS) 14 (4), 1-30, 2021.

   

Gund, Manasi, Abhiram Ravi Bharadwaj, and Ifeoma Nwogu. "Interpretable Emotion Classification Using Temporal Convolutional Models." In 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6367-6374. IEEE Computer Society, 2021.

Ananthanarayana, Tejaswini, Lipisha Chaudhary, and Ifeoma Nwogu. "Effects of feature scaling and fusion on sign language translation." In Proc. Interspeech, pp. 2292-2296. 2021.

Carver, William, and Ifeoma Nwogu. "Facial Expression Neutralization With StoicNet." In 2021 IEEE Winter Conference on Applications of Computer Vision Workshops (WACVW), pp. 201-208. IEEE Computer Society, 2021.

   
 

 

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Boveda-Lambie, Adriana M.; Tuten, Tracy; and Perotti, Victor (2021) "To Share or Not to Share? Branded Content Sharing in Twitter," Atlantic Marketing Journal: Vol. 10 : No. 2 , Article 4.

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Publications:
Tejaswini Ananthanarayana, Priyanshu Srivastava, Akash Chintha, Akhil Santha, Brian Landy, Joseph Panaro, Andre Webster, Nikunj Kotecha, Shagan Sah, Thomastine Sarchet, Raymond Ptucha, Ifeoma Nwogu.  “Deep learning methods for sign language translation.” ACM Transactions on Accessible Computing (TACCESS) 14 (4), 1-30, 2021.

   

Abhishek Vashist, Maojia Patrick Li, Amlan Ganguly, Clark Hochgraf, Raymond Ptucha, Andres Kwasinski, Michael E Kuhl. “KF-Loc: A Kalman Filter and Machine Learning Integrated Localization System Using Consumer-Grade Millimeter-wave Hardware.” IEEE Consumer Electronics Magazine, doi: 10.1109/MCE.2021.3101060.

 

Miguel Dominguez and Raymond Ptucha. "Directional Graph Networks with Hard Weight Assignments." In 2020 25th International Conference on Pattern Recognition (ICPR), pp. 7439-7446. IEEE, 2021.

Patents:
Raymond William Ptucha, Alexander C. Loui
, Mark D. Wood, David K. Rhoda, David Kloosterman, and Joseph Anthony Manico. "Imaging workflow using facial and non-facial features." U.S. Patent 11,182,590, issued November 23, 2021.

Chi Zhang, Raymond Ptucha, Alexander Loui, and Carl Salvaggio. "System and method for batch-normalized recurrent highway networks." U.S. Patent Application 17/126,745, filed April 8, 2021.

Raymond W. Ptucha, William J. Bogart, and Laura R. Whitby. "Group display system." U.S. Patent Application 17/107,076, filed March 18, 2021.

Felipe Petroski Such, Raymond Ptucha, Frank Brockler, Paul Hutkowski, and Vatsala Singh. "System and method of character recognition using fully convolutional neural networks." U.S. Patent 10,936,862, issued March 2, 2021.

Felipe Petroski Such, Raymond Ptucha, Frank Brockler, and Paul Hutkowski. "System and method of character recognition using fully convolutional neural networks with attention." U.S. Patent Application 17/075,513, filed February 4, 2021.

Felipe Petroski Such, Raymond Ptucha, Frank Brockler, and Paul Hutkowski. "System and method of character recognition using fully convolutional neural networks with attention." U.S. Patent Application 17/075,511, filed February 4, 2021.

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Kulomäki, J., Oksama, L., Rantanen E., Hyönä, J. Attention control in a demanding dynamic time-sharing environment: An eye-tracking study. Attention, Perception, & Psychophysics Sep 30:1-20, 2021.

Zhang, Y.Z , Rantanen, E. M., & Chignell, M.  Student perspectives on changing requirements for human factors engineering education. Proceedings of the Human Factors and Ergonomics Society 2021 Annual Meeting. 65(1): 1579-1583, 2021.

Rantanen, E. M., Lee, J. D., Darveau, K., Miller, D. B., Intriligator, J., & Sawyer, B. D. Ethics education of human factors engineers for responsible AI development. Proceedings of the Human Factors and Ergonomics Society 2021 Annual Meeting 65(1): 1034-1038, 2021.

Karn, K. S., Rantanen, E. M., Branaghan, R. J., Rayo, M. F., Sanchez, C. A., & Lum, H. C. Practitioner-educator model for human factors/ergonomics education. Proceedings of the Human Factors and Ergonomics Society 2021 Annual Meeting, 65(1): 53-56, 2021.

Rantanen, E. M., & Huijbrechts, J-E. (2021). Procedures as an ecological interface. Proceedings of the 21st International Symposium on Aviation Psychology (pp. 310–315). Virtual, May 18-21, 2021. https://doi.org/10.5399/osu/1148

Rantanen, E. M., & Huijbrechts, J-E. (2021). Organizational safety in airline operations. Proceedings of the 21st International Symposium on Aviation Psychology (pp. 190–195). Virtual, May 18-21, 2021. https://doi.org/10.5399/osu/1148

 

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Kumra, Sulabh, Shirin Joshi, and Ferat Sahin. "Learning Multi-step Robotic Manipulation Policies from Visual Observation of Scene and Q-value Predictions of Previous Action." arXiv preprint arXiv:2202.11280 (2022).

Kumra, Sulabh, Shirin Joshi, and Ferat Sahin. "Learning Robotic Manipulation Tasks via Task Progress Based Gaussian Reward and Loss Adjusted Exploration." IEEE Robotics and Automation Letters 7.1 (2021): 534-541.

Kumra, Sulabh, Shirin Josh, and Ferat Sahin. "Learning robotic manipulation tasks through visual planning." arXiv preprint arXiv:2103.01434 (2021).

 

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B. Artacho and A. Savakis, Unipose+: A unified framework for 2D and 3D human pose estimation in images and videos. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021.

A. Taufique and A Savakis, “LABNet: Local graph aggregation network with class balanced loss for vehicle re-identification,” Neurocomputing, 2021.

N. Nagananda, A. Taufique, R. Madappa, S Jahan, B. Minnehan, T. Rovito, A. Savakis, “Benchmarking Domain Adaptation Methods on Aerial Datasets,” Sensors 2021.

U. Sharma, B. Artacho, A. Savakis, “GourmetNet: Food Segmentation Using Multi-Scale Waterfall Features with Spatial and Channel Attention,” Sensors 2021,

H. Chen, A. Savakis, A. Diehl, E. Blasch, S. Wei and G. Chen, “Targeted Adversarial Discriminative Domain Adaptation,” Journal of Applied Remote Sensing, 2021.

C. Lusardi, A. Taufique and A. Savakis, “Robust Multi-Object Tracking Using Re-Identification Features and Graph Convolutional Networks,” IEEE/CVF International Conference on Computer Vision (ICCV) Workshop on Analysis of Aerial Motion Imagery (WAAMI), 2021.

N. Nagananda and A. Savakis, “GILDA++: Grassmann Incremental Linear Discriminant Analysis,” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshop on Differential Geometry in Computer Vision and Machine Learning (DiffCVML), 2021.

D. Gupta, B. Artacho and A. Savakis, “VehiPose: a multi-scale framework for vehicle pose estimation,” SPIE Optical Engineering and Applications, Applications of Digital Image Processing XLIV, 2021.

A. Taufique, A. Savakis, M. Braun, D. Kubacki, E. Dell, L. Qian, S. O'Rourke, “SiamReID: Confuser Aware Siamese Tracker with Re-identification Feature,” SPIE Optical Engineering and Applications, Applications of Machine Learning, 2021.

N. Pandey, A. Savakis, “Extreme Face Inpainting with Sketch-Guided Conditional GAN,” Electronic Imaging, Computational Imaging Conference, Jan. 2021.

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Staib,L.H. and Shi,P.: Special Issue on MICCAI 2019, Medical Image Analysis, 70, May, 2021.

Bondy,C., Chen,L., Grover,P/, Hanson,V., Li,R, and Shi,P.: Evaluating Technology-Mediated Collaborative Workflows for Telehealth, IEEE Journal of Biomedical and Health Informatics, 25(12): 4308-4316, December, 2021. DOI: 10.1109/JBHI.2021.3119458.

Zheng,E., Yu,Q., Li,R., Shi,P., and Haake,A.R.: A Continual Learning Framework for Uncertainty-Aware Interactive Image Segmentation, The AAAI Conference on Artificial Intelligence (AAAI), 2021.

Cueva,F., Shi,P., and Cedillo,P.: A Data-Driven Optimization Computational Tool Design for Bike-Sharing Station Distribution in Small to Medium-Sized Cities: A Case Study for Cuenca, Ecuador, Information Systems Development (ISD), Valencia, Spain, September, 2021.

 

Gyawali, Prashnna K, Jaideep Vitthal Murkute, Maryam Toloubidokhti, Xiajun
Jiang, B. Milan Horacek, John L. Sapp, and Linwei Wang. “Learning to
Disentangle Inter-Subject Anatomical Variations in Electrocardiographic Data.”
IEEE Transactions on Biomedical Engineering, 2021, 1–1.
https://doi.org/10.1109/TBME.2021.3108164.

Lousto, Carlos O, Ryan Missel, Harshkumar Prajapati, Valentina Sosa Fiscella,
Federico G López Armengol, Prashnna Kumar Gyawali, Linwei Wang, et al.
“Vela Pulsar: Single Pulses Analysis with Machine Learning Techniques.”
Monthly Notices of the Royal Astronomical Society 509, no. 4 (December 15,
2021): 5790–5808. https://doi.org/10.1093/mnras/stab3287.

Zaman, Md Shakil, Jwala Dhamala, Pradeep Bajracharya, John L. Sapp, B.
Milan Horacek, Katherine C. Wu, Natalia A. Trayanova, and Linwei Wang. “Fast
Posterior Estimation of Cardiac Electrophysiological Model Parameters via
Bayesian Active Learning.” ArXiv:2110.06851 [Cs], October 13, 2021.
http://arxiv.org/abs/2110.06851.

Aakash Saboo, Prashnna K Gyawali, Ankit Shukla, Neeraj Jain, Manoj Sharma,
and Linwei Wang, Latent-optimization Based Disease-Aware Image Editing for
Medical Image Augmentation, British Machine Vision Conference (BMVC) 2021.

*Xiajun Jiang, *Ryan Missel, Maryam Toloubidokhi, Zhiyuan Li, Omar Gharbia, John L. Sapp, and Linwei Wang. Label-Free Physics-Informed Image Sequence
Reconstruction with Disentangled Spatial-Temporal Modeling. Medical Image
Computing and Computer-Assisted Intervention (MICCAI), 2021, accepted.(*equal contribution)

Maryam Toloubidokhti, Prashnna K. Gyawali, Omar A. Gharbia, Xiajun Jiang, Jaume Coll-Font, Jake Bergquist, Brian Zenger, Wilson W. Good, Dana H. Brooks, Rob S. MacLeod, and Linwei Wang, Deep Adaptive Electrocardiographic Imaging with Generative Forward Model for Error Reduction, Functional Imaging and Modeling of the Heart (FIMH), accepted, 2021.

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Krishna Neupane, Ervine Zheng, Yu Kong, and Qi Yu: A Dynamic Meta-Learning Model for Time-Sensitive Cold-Start Recommendations, AAAI 2022 (Acceptance rate: 15%).

Weishi Shi, Dayou Yu, and Qi Yu: A Gaussian Process-Bayesian Bernoulli Mixture Model for Multi-Label Active Learning, NeurIPS 2021 (Acceptance rate: 26%).

Dingrong Wang, Hitesh Sapkota, Xumin Liu, and Qi Yu: Deep Reinforced Attention Regression for Partial Sketch Based Image Retrieval, ICDM 2021, Full paper, 10 pages (Acceptance rate: 9.9%).

Krishna Neupane, Ervine Zheng, and Qi Yu: MetaEDL: Meta Evidential Learning For Uncertainty-Aware Cold-Start Recommendations, ICDM 2021, Short paper, 6 pages (Acceptance rate: 20%).

Yuansheng Zhu, Weishi Shi, Deep Pandey, Yang Liu, Xiaofan Que, Daniel Krutz, and Qi Yu, Uncertainty-Aware Multiple Instance Learning from Large-Scale Long Time Series Data. IEEE BigData, 2021, (Acceptance rate: 19.7%).

Niranjana Deshpande, Naveen Sharma, Qi Yu and Daniel Krutz: R-CASS: Using Algorithm Se- lection for Self-Adaptive Service Oriented Systems, ICWS 2021: 61-72, Best paper award [1 out of 194] (Acceptance rate: 23.7%).

W. Bao, Q. Yu, Y. Kong: Evidential Deep Learning for Open Set Action Recognition. ICCV 2021: 13349-13358 (Acceptance rate: 25.9%).

W. Bao, Q. Yu, Y. Kong: DRIVE: Deep Reinforced Accident Anticipation with Visual Explanation. ICCV 2021: 7619-7628, Oral, (Acceptance rate: 3%).

Hitesh Sapkota, Yiming Ying, Feng Chen, Qi Yu: Distributionally Robust Optimization for Deep Kernel Multiple Instance Learning. AISTATS 2021: 2188-2196. (Acceptance rate: 29%).

Weishi Shi and Qi Yu: Active Learning with Maximum Margin Sparse Gaussian Processes. AIS- TATS 2021: 406-414. (Acceptance rate: 29%).

Ervine Zheng, Qi Yu, Rui Li, Pengcheng Shi, Anne R. Haake: A Continual Learning Framework for Uncertainty-Aware Interactive Image Segmentation. AAAI 2021: 6060-6038 (Acceptance rate: 21%).

 
 
 
 
 
 
 
 
 
 

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EA AlOmar, J Liu, K Addo, MW Mkaouer, C Newman, A Ouni, Z Yu. On the documentation of refactoring types. Automated Software Engineering 29 (1), 1-40,2022.

 

E Abdullah AlOmar, J Liu, K Addo, M Wiem Mkaouer, C Newman, A Ouni, Z Yu.  On the Documentation of Refactoring Types. arXiv e-prints, arXiv: 2112.01581, 2021.

 

Z Yu. Fair Balance: Mitigating Machine Learning Bias Against Multiple Protected Attributes With Data Balancing. arXiv preprint arXiv:2107.08310, 2021.

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Nie, Guangtao, Akshith Ullal, Zhi Zheng, Amy R. Swanson, Amy S. Weitlauf, Zachary E. Warren, and Nilanjan Sarkar. "An Immersive Computer-Mediated Caregiver-Child Interaction System for Young Children With Autism Spectrum Disorder." IEEE Transactions on Neural Systems and Rehabilitation Engineering 29 (2021): 884-893.

Koirala, Ankit, Zhiwei Yu, Hillary Schiltz, Amy Van Hecke, Brian Armstrong, and Zhi Zheng. "A Preliminary Exploration of Virtual Reality-Based Visual and Touch Sensory Processing Assessment for Adolescents With Autism Spectrum Disorder." IEEE Transactions on Neural Systems and Rehabilitation Engineering 29 (2021): 619-628.

Zhiwei Yu, Cory Crane, Maria Testa, Zhi Zheng. “How Moderate Alcohol Consumption Impacts Cohabiting Couples in Expressing Disagreements: An Automatic Computation Model and Analysis.” The 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, 2021.

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