Hemanth Venkateswara
Hemanth Venkateswara
Assistant Professor, Georgia State University
Verified email at - Homepage
Cited by
Cited by
Deep Hashing Network for Unsupervised Domain Adaptation
H Venkateswara, J Eusebio, S Chakraborty, S Panchanathan
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
Other Adaptations
VN Balasubramanian, P Lade, H Venkateswara, E Smirnov, ...
Morgan Kaufmann, 2014
Leveraging Seen and Unseen Semantic Relationships for Generative Zero-shot Learning
MR Vyas, H Venkateswara, S Panchanathan
European Conference on Computer Vision (ECCV), 70-86, 2020
Deep-learning Systems for Domain Adaptation in Computer Vision: Learning Transferable Feature Representations
H Venkateswara, S Chakraborty, S Panchanathan
IEEE Signal Processing Magazine 34 (6), 117-129, 2017
Deep Active Learning for Image Classification
H Ranganathan, H Venkateswara, S Chakraborty, S Panchanathan
2017 IEEE International Conference on Image Processing (ICIP), 3934-3938, 2017
A Strategy for an Uncompromising Incremental Learner
R Venkatesan, H Venkateswara, S Panchanathan, B Li
CoRR, 2017
Whistle-blowing ASRs: Evaluating the Need for More Inclusive Speech Recognition Systems
M Moore, H Venkateswara, S Panchanathan
Proc. Interspeech 2018, 466-470, 2018
Coupling Adversarial Learning with Selective Voting Strategy for Distribution Alignment in Partial Domain Adaptation
S Choudhuri, H Venkateswara, A Sen
Journal of Computational and Cognitive Engineering 1 (4), 181-186, 2022
Say What? A Dataset for Exploring the Error Patterns That Two ASR Engines Make
M Moore, M Saxon, H Venkateswara, V Berisha, S Panchanathan
Proc. Interspeech 2019, 2528-2532, 2019
Efficient Approximate Solutions to Mutual Information Based Global Feature Selection
H Venkateswara, P Lade, B Lin, J Ye, S Panchanathan
Proc. of IEEE International Conference on Data Mining (ICDM), 1009-1014, 2015
Deep Active Learning for Image Regression
H Ranganathan, H Venkateswara, S Chakraborty, S Panchanathan
Deep Learning Applications, 113-135, 2020
Improving Communication Skills of Children With Autism Through Support of Applied Behavioral Analysis Treatments Using Multimedia Computing: A Survey
CDC Heath, T McDaniel, H Venkateswara, S Panchanathan
Universal Access in the Information Society, 1-18, 2020
Detecting Attention in Pivotal Response Treatment Video Probes
CDC Heath, H Venkateswara, T McDaniel, S Panchanathan
Smart Multimedia (ICSM), 248-259, 2018
Coupled Support Vector Machines for Supervised Domain Adaptation
H Venkateswara, P Lade, J Ye, S Panchanathan
Proceedings of the 23rd ACM International Conference on Multimedia (ACM-MM …, 2015
Domain Adaptation in Computer Vision with Deep Learning
H Venkateswara, S Panchanathan
Springer International Publishing, 2020
Partial Domain Adaptation Using Selective Representation Learning For Class-Weight Computation
S Choudhuri, R Paul, A Sen, B Li, H Venkateswara
IEEE Asilomar Conf. on Signals, Systems and Computers, 2021
Introduction to domain adaptation
H Venkateswara, S Panchanathan
Domain adaptation in computer vision with deep learning, 3-21, 2020
Detection of Changes in Human Affect Dimensions Using an Adaptive Temporal Topic Model
P Lade, VN Balasubramanian, H Venkateswara, S Panchanathan
Proc. of IEEE International Conference on Multimedia and Expo (ICME), 1-6, 2013
Glocal alignment for unsupervised domain adaptation
S Chhabra, PB Dutta, B Li, H Venkateswara
Multimedia Understanding with Less Labeling on Multimedia Understanding with …, 2021
Smart Stadia as Testbeds for Smart Cities: Enriching Fan Experiences and Improving Accessibility
S Panchanathan, T McDaniel, R Tadayon, A Rukkila, H Venkateswara
Proc. of IEEE International Conference on Computing, Networking and …, 2019
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