2 citations · 2 across the 4 of their papers we have counts for
4 papers
Exploring Dropout Discriminator for Domain Adaptation
Vinod K Kurmi, Venkatesh K Subramanian, Vinay P. Namboodiri
Adaptation of a classifier to new domains is one of the challenging problems in machine learning. This has been addressed using many deep and non-deep learning based methods. Among…
A Framework for Enabling Safe and Resilient Food Factories for the Public Feeding Programs
Nataraj Kuntagod, Sanjay Podder, Satya Sai Srinivas Abbabathula +3
Public feeding programs continue to be a major source of nutrition to a large part of the population across the world. Any disruption to these activities, like the one during the C…
Domain Impression: A Source Data Free Domain Adaptation Method
Vinod K Kurmi, Venkatesh K Subramanian, Vinay P Namboodiri
Unsupervised Domain adaptation methods solve the adaptation problem for an unlabeled target set, assuming that the source dataset is available with all labels. However, the availab…
Do Not Forget to Attend to Uncertainty while Mitigating Catastrophic Forgetting
Vinod K Kurmi, Badri N. Patro, Venkatesh K. Subramanian +1
One of the major limitations of deep learning models is that they face catastrophic forgetting in an incremental learning scenario. There have been several approaches proposed to t…