Computer Vision
We focus on self-supervised and human-machine collaborative learning of robust representations using contrastive, zero-shot, and multimodal learning.
Funded Projects
- Heterogeneous Hypergraph Modeling for Zero-shot Product Aspect Identification – ebay 2024
- A data-driven multiscale phytotechnology framework for identification and remediation of leached-metals-contaminated soil near coal ash impoundments – DOE 2022
- Reducing Operating Room Waste by Monitoring Single-use Sterile Surgical Supplies with Computer Vision – NIH iTHRIV 2021
- Determination of Safety Limits against Cyber Threats in Neuromodulation Devices using Machine Learning, Brain Phantoms, and Neural Pathways – Commonwealth Cyber Initiative (CCI) 2021
- Intelligent Augmented Reality for the Future of Work – VT ICTAS EFO 2021
- Intelligent Augmented Reality for the Future of Work – VT CHCI 2021
- Pull-Off Arm and Vibration Stoppers Detection – Japan Rail East Information Systems 2018
- Augmented Reality Assistant – Xerox 2017
- Automating Evaluation of Product Efficacy – Procter and Gamble 2017
- Connected Consumer for Enhancing Product Experience – Procter and Gamble 2016
Publications
2024
[p1] System and Method using Augmented Reality for Efficient Collection of Training Data for Machine Learning
M. Shreve, S. Kumar, J. Sun, G. Gavai, R. Price, and H. Eldardiry
PATENT 11978243 GRANTED 2024
2023
[c1] Prediction of Electric Fields Induced by Transcranial Magnetic Stimulation in the Brain using a Deep Encoder-Decoder Convolutional Neural Network
M. Tashli, M. Alam, J. Gong, C. Lewis, C. Peterson, H. Eldardiry, J. Atulasimha, and R. Hadimani
IEEE Internation EMBS Conference on Neural Engineering 2023
Acceptance Rate 24%
[c2] Prediction of Electric Fields Induced by Transcranial Magnetic Stimulation in the Brain using a Deep Encoder-Decoder Convolutional Neural Network
M. Tashli, M. Alam, J. Gong, C. Lewis, C. Peterson, H. Eldardiry, J. Atulasimha, R. Hadimani
Bulletin of the American Physical Society 2023
2022
[p2] System and Method for Performing Collaborative Learning of Machine Representations for a Target Concept
F. Torres and H. Eldardiry
PATENT 17/207385 PUBLISHED 2022
[p3] Method, System, and Manufacture for Inferring User Lifestyle and Preference Information from Images
R. Price, A. Roy, and H. Eldardiry
PATENT 11334933 GRANTED 2022
[c3] Prediction of Stimulation Strength of Transcranial Magnetic Stimulation in the Brain with Deep Convolutional Neural Network based Encoder-Decoder Network
M. Alam, M. Tashli, J. Gong, C. Lewis , C. Peterson, H. Eldardiry, R. Hadimani, J. Atulasimha
IEEE Conference on Magnetism and Magnetic Materials 2022
[i1] Hard Negative Sampling Strategies for Contrastive Representation Learning
A. Tabassum, M. Wahed, H. Eldardiry, and I. Lourentzou
arXiv.2206.01197 2022
2021
[p4] Agile Video Query using Ensembles of Deep Neural Nets
F. Torres, H. Eldardiry, M. Shreve, G. Gavai, and C. Ramos
PATENT 11093798 GRANTED 2021
2019
[c4] Hybrid Image-based Defect Detection for Railroad Maintenance
G. Gavai, H. Eldardiry, W. Wu, B. Xu, Y. Komatsu, and S. Makino
Society for Imaging Science and Technology Electronic Imaging Symposium 2019
[c5] Collaborative Learning of Concept Representations for Video Data
F. Torres, H. Eldardiry, G. Gavai, and C. Ramos
AAAI Spring Symposium on Combining Machine Learning with Knowledge Engineering (AAAI-MAKE) 2019
