36 citations · 46 across the 7 of their papers we have counts for
7 papers
WaveFuse-AL: Cyclical and Performance-Adaptive Multi-Strategy Active Learning for Medical Images
Nishchala Thakur, Swati Kochhar, Deepti R. Bathula +1
Active learning reduces annotation costs in medical imaging by strategically selecting the most informative samples for labeling. However, individual acquisition strategies often e…
Understanding Calibration of Deep Neural Networks for Medical Image Classification
Abhishek Singh Sambyal, Usma Niyaz, Narayanan C. Krishnan +1
In the field of medical image analysis, achieving high accuracy is not enough; ensuring well-calibrated predictions is also crucial. Confidence scores of a deep neural network play…
Leveraging Different Learning Styles for Improved Knowledge Distillation in Biomedical Imaging
Usma Niyaz, Abhishek Singh Sambyal, Deepti R. Bathula
Learning style refers to a type of training mechanism adopted by an individual to gain new knowledge. As suggested by the VARK model, humans have different learning preferences, li…
IPNET:Influential Prototypical Networks for Few Shot Learning
Ranjana Roy Chowdhury, Deepti R. Bathula
Prototypical network (PN) is a simple yet effective few shot learning strategy. It is a metric-based meta-learning technique where classification is performed by computing Euclidea…
Influential Prototypical Networks for Few Shot Learning: A Dermatological Case Study
Ranjana Roy Chowdhury, Deepti R. Bathula
Prototypical network (PN) is a simple yet effective few shot learning strategy. It is a metric-based meta-learning technique where classification is performed by computing Euclidea…
Augmenting Knowledge Distillation With Peer-To-Peer Mutual Learning For Model Compression
Usma Niyaz, Deepti R. Bathula
Knowledge distillation (KD) is an effective model compression technique where a compact student network is taught to mimic the behavior of a complex and highly trained teacher netw…
Towards Reducing Aleatoric Uncertainty for Medical Imaging Tasks
Abhishek Singh Sambyal, Narayanan C. Krishnan, Deepti R. Bathula
In safety-critical applications like medical diagnosis, certainty associated with a model's prediction is just as important as its accuracy. Consequently, uncertainty estimation an…