6 citations · 7 across the 10 of their papers we have counts for
6 papers · 1 filter
MetaErr: Towards Predicting Error Patterns in Deep Neural Networks
Varun Totakura, Shayok Chakraborty
Due to the unprecedented success of deep learning, it has become an integral component in several multimedia computing applications in todays world. Unfortunately, deep learning sy…
ACIL: Active Class Incremental Learning for Image Classification
Aditya R. Bhattacharya, Debanjan Goswami, Shayok Chakraborty
Continual learning (or class incremental learning) is a realistic learning scenario for computer vision systems, where deep neural networks are trained on episodic data, and the da…
D3GU: Multi-Target Active Domain Adaptation via Enhancing Domain Alignment
Lin Zhang, Linghan Xu, Saman Motamed +2
Unsupervised domain adaptation (UDA) for image classification has made remarkable progress in transferring classification knowledge from a labeled source domain to an unlabeled tar…
Active Learning for Video Classification with Frame Level Queries
Debanjan Goswami, Shayok Chakraborty
Deep learning algorithms have pushed the boundaries of computer vision research and have depicted commendable performance in a variety of applications. However, training a robust d…
Nonlinear Embedding Transform for Unsupervised Domain Adaptation
Hemanth Venkateswara, Shayok Chakraborty, Sethuraman Panchanathan
The problem of domain adaptation (DA) deals with adapting classifier models trained on one data distribution to different data distributions. In this paper, we introduce the Nonlin…
Deep Hashing Network for Unsupervised Domain Adaptation
Hemanth Venkateswara, Jose Eusebio, Shayok Chakraborty +1
In recent years, deep neural networks have emerged as a dominant machine learning tool for a wide variety of application domains. However, training a deep neural network requires a…