Hemanth D Venkateswara

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Publications

Complete list of publications is available at Google Scholar

Journals

  1. C. Heath, T. McDaniel, H. Venkateswara and S. Panchanathan, Improving Communication Skills of Children With Autism Through Support of Applied Behavioral Analysis Treatments Using Multimedia Computing: A Survey, Universal Access in the Information Society, 2020. [Link] [Bibtex]

  2. H. Venkateswara, T. McDaniel, R. Tadayon and S. Panchanathan, Person-centered Technologies for Individuals with Disabilities: Empowerment Through Assistive and Rehabilitative Solutions, Special Issue: Technology & Innovation Journal, Natl. Academy of Inventors , Vol.20, pp. 117-132, 2018. [PDF] [Bibtex]

  3. H. Venkateswara, S. Chakraborty and S. Panchanathan, Deep Learning Systems for Domain Adaptation in Computer Vision: Learning Transferable Feature Representations, IEEE Signal Processing Magazine, 34 (6), 117-129, Nov 2017. [Link] [Bibtex]

Conferences and Workshops

  1. S. Chhabra, H. Venkateswara and B. Li, Generative Alignment of Posterior Probabilities for Source-free Domain Adaptation, Winter Conf. on Applications in Computer Vision (WACV), 2023.

  2. S. Chhabra, P. B. Dutta, H. Venkateswara and B. Li, PatchRot: A Self-Supervised Technique for Training Vision Transformers, (NeurIPS 2022 Workshops), 1st Workshop on Vision Transformers: Theory and Applications (VTTA), 2022. [PDF]

  3. S. Chhabra, H. Venkateswara and B. Li, PatchSwap: A Regularization Technique for Vision Transformers, British Machine Vision Conf. (BMVC), 2022.

  4. S. Choudhuri, S. Adeniye, A. Sen and H. Venkateswara, Domain-Invariant Feature Alignment Using Variational Inference For Partial Domain Adaptation, IEEE Asilomar Conf. on Signals, Systems and Computers, 2022.

  5. V. Kakaraparthi, T. McDaniel, H. Venkateswara and M. Goldberg, PERACTIV: Personalized Activity Monitoring - Ask My Hands, Human Computer Interaction International (HCII), pp. 255-272, Online, 2022. [Link]

  6. S. Choudhuri, H. Venkateswara and A. Sen, Coupling Adversarial Learning with Selective Voting Strategy for Distribution Alignment in Partial Domain Adaptation, (KDD 2022 Workshops), 4th Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML), 2022. [PDF]

  7. N. S. Uppara, T. McDaniel and H. Venkateswara, Effect of Image Captioning with Description on the Working Memory, Human Computer Interaction International (HCII), pp. 207-120, Online, 2021. [Link]

  8. S. Chhabra, P. B. Dutta, B. Li and H. Venkateswara, Glocal Alignment for Unsupervised Domain Adaptation, (ACMMM 2021 Workshops) ACM Multimedia 2021 Workshop on Multimedia Understanding with Less Labeling (MULL), 2021.

  9. S. Chhabra, B. Li and H. Venkateswara, Iterative Image Translation for Unsupervised Domain Adaptation, (ACMMM 2021 Workshops), ACM Multimedia 2021 Workshop on Multimedia Understanding with Less Labeling (MULL), 2021.

  10. S. Choudhuri, R. Paul, A. Sen, B. Li and H. Venkateswara, Partial Domain Adaptation Using Selective Representation Learning For Class-Weight Computation, IEEE Asilomar Conf. on Signals, Systems and Computers, Virtual, 2020. [PDF] [Link]

  11. M. R. Vyas, H. Venkateswara and S. Panchanathan, Leveraging Seen and Unseen Semantic Relationships for Generative Zero-shot Learning, European Conference on Computer Vision, (ECCV-20), Glasgow (Virtual), 2020. [PDF] [Bibtex] [CODE]

  12. A. Dudley, B. Nagabandi, H. Venkateswara and S. Panchanathan, Domain Adaptive Fusion for Adaptive Image Classification, Intl. Conf. on Smart Multimedia (ICSM), San Diego, CA, 2019. [Link] [Bibtex]

  13. B. Nagabandi, A. Dudley, H. Venkateswara and S. Panchanathan, Certain and Consistent Domain Adaptation, Intl. Conf. on Smart Multimedia (ICSM), San Diego, CA, 2019. [Link] [Bibtex]

  14. B. Fakhri, T. McDaniel, H. B. Amor, H. Venkateswara, A. Chowdhury and S. Panchanathan, Foveated Haptic Gaze, Intl. Conf. on Smart Multimedia (ICSM), San Diego, CA, 2019. [PDF] [Bibtex]

  15. C. Heath, T. Heath, T. McDaniel, H. Venkateswara and S. Panchanathan, Using Participatory Design to Create a User Interface for Analyzing Pivotal Response Treatment Video Probes, Intl. Conf. on Smart Multimedia (ICSM), San Diego, CA, 2019. [Link] [Bibtex]

  16. C. Heath, H. Venkateswara, T. McDaniel and S. Panchanathan, Using Multimodal Data for Automated Fidelity Evaluation in Pivotal Response Treatment Videos, Symposium on Signal and Information Processing for Person-centered and Citizen-centered Smart Living held in conjunction with 7th IEEE Global Conference on Signal and Information Processing (GlobalSIP), Ottawa, Canada, 2019. [Link] [Bibtex]

  17. P. Papreja, H. Venkateswara and S. Panchanathan, Representation, Exploration and Recommendation of Music Playlists, 12th International Workshop on Machine Learning and Music (MML) at (ECML/PKDD-19 Workshops), Wurzburg, Germany, 2019. [PDF] [Bibtex]

  18. M. Moore, M. Saxon, H. Venkateswara, V. Berisha and S. Panchanathan, Say What? A Dataset for Exploring the Error Patterns That Two ASR Engines Make, Proc. of the Annual Conference of the International Speech Communication Association, INTERSPEECH, Graz, Austria, (INTERSPEECH-19) 2019. [PDF] [Bibtex]

  19. C. Heath, T. McDaniel, H. Venkateswara and S. Panchanathan, Parent and Child Voice Activity Detection in Pivotal Response Treatment Video Probes, Human-Computer Interaction International (HCII), pp. 270-286, Orlando, FL, 2019. [Link] [Bibtex]

  20. C. Heath, H. Venkateswara and S. Panchanathan, Are You Paying Attention? Classifying Attention in Pivotal Response Treatment Videos, IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) Workshops}, Long Beach, CA, (CVPR-19 Workshops), 2019. [PDF] [Bibtex]

  21. S. Panchanathan, T. McDaniel, R. Tadayon, A. Rukkila and H. Venkateswara, Smart Stadia as Testbeds for Smart Cities: Enriching Fan Experiences and Improving Accessibility, Intl. Conf. on Computing, Networking and Communications (ICNC), pp. 542-546, Honolulu, Hawaii, 2019. [Link] [Bibtex]

  22. H. Ranganathan, H. Venkateswara, S. Chakraborty and S. Panchanathan, Multi-label Deep Active Learning with Label Correlation, IEEE Intl. Conf. on Image Processing (ICIP), Athens, Greece, 2018. [Link] [Bibtex]

  23. C. Heath, H. Venkateswara, T. McDaniel and S. Panchanathan, Detecting Attention in Pivotal Response Treatment Video, Intl. Conf. on Smart Multimedia (ICSM), pp. 248-259, Toulon, Cote D'Azur, France, 2018. [Link] [Bibtex]

  24. S. Panchanathan, R. Tadayon, H. Venkateswara and T. McDaniel, Person-centric Multimedia: How Research Inspirations from Designing Solutions for Individual Users Benefits the Broader Population, Intl. Conf. on Smart Multimedia (ICSM), pp. 51-65, Toulon, Cote D'Azur, France, 2018. [Link] [Bibtex]

  25. J. Eusebio, H. Venkateswara, and S. Panchanathan, Semi-supervised Adversarial Image-to-Image Translation, Intl. Conf. on Smart Multimedia (ICSM), pp. 334-344, Toulon, Cote D'Azur, France, 2018. [Link] [Bibtex]

  26. B. Fakhri, A. Keech, J. Schlosser, E. Brooks, H. Venkateswara, S. Panchanathan and Z. Kira, Deep Reinforcement Learning Methods for Navigational Aids, Intl. Conf. on Smart Multimedia (ICSM), pp. 66-75, Toulon, Cote D'Azur, France, 2018. [Link] [Bibtex]

  27. M. Moore, H. Venkateswara, and S. Panchanathan, Whistle-blowing ASRs: Evaluating the Need for More Inclusive Automatic Speech Recognition Systems, Proc. of the Annual Conference of the International Speech Communication Association, INTERSPEECH, Hyderabad, India, (INTERSPEECH-18), 2018. [PDF] [Bibtex]

  28. H. Venkateswara, J. Eusebio, S. Chakraborty and S. Panchanathan, Deep Hashing Network for Unsupervised Domain Adaptation, IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 5018-5027, Honolulu, Hawaii, (CVPR-17), 2017. [PDF] [Bibtex] [OfficeHome Dataset] [CODE]

  29. H. Ranganathan, H. Venkateswara, S. Chakraborty and S. Panchanathan, Deep Active Learning for Image Classification, IEEE Intl. Conf. on Image Processing (ICIP), pp. 3934-3938, Beijing, China, 2017. [Link] [Bibtex]

  30. H. Venkateswara, S. Chakraborty, T. McDaniel and S. Panchanathan, Model Selection with Nonlinear Embedding for Unsupervised Domain Adaptation, KnowPros Workshop AAAI Conf., San Francisco, CA, (AAAI-17 Workshops), 2017. [PDF] [Bibtex]

  31. H. Venkateswara, S. Chakraborty and S. Panchanathan, Nonlinear Embedding Transform for Unsupervised Domain Adaptation, TASKCV Workshop, European Conf. on Computer Vision (ECCV)}, Amsterdam, Netherlands, (ECCV-16, Workshops), 2016. [PDF] [Bibtex]

  32. H. Venkateswara, P. Lade, B. Lin, J. Ye and S. Panchanathan, Efficient Approximate Solutions to Mutual Information Based Global Feature Selection, IEEE Intl. Conf. on Data Mining (ICDM), Atlantic City, NJ, 2015. [PDF] [Bibtex]

  33. H. Venkateswara, P. Lade, J. Ye and S. Panchanathan, Coupled Support Vector Machines for Supervised Domain Adaptation, ACM Conf. on Multimedia (ACM-MM), Brisbane, Australia, (ACMMM-15), 2015. [PDF] [Bibtex]

  34. H. Venkateswara, V. N. Balasubramanian, P. Lade and S. Panchanathan, Multiresolution Match Kernels for Gesture Video Classification, IEEE Intl. Conf. on Multimedia and Expo Workshops (ICMEW), San Jose, CA, 2013. [PDF] [Bibtex]

  35. S. Chakraborty, H. Venkateswara, V. N. Balasubramanian and S. Panchanathan, Active Batch Selection for Fuzzy Classification in Facial Expression Recognition, Intl. Conf. on Machine Learning Applications (ICMLA), Honolulu, Hawaii, 2011. [Link] [Bibtex]