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20212024
most citedData efficient deep learning for medical image analysis: A survey

4 citations · 8 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2024

Reliable or Deceptive? Investigating Gated Features for Smooth Visual Explanations in CNNs

Soham Mitra, Atri Sukul, Swalpa Kumar Roy +2

Deep learning models have achieved remarkable success across diverse domains. However, the intricate nature of these models often impedes a clear understanding of their decision-ma…

cs.CV20243 cited

LG-Traj: LLM Guided Pedestrian Trajectory Prediction

Pranav Singh Chib, Pravendra Singh

Accurate pedestrian trajectory prediction is crucial for various applications, and it requires a deep understanding of pedestrian motion patterns in dynamic environments. However,…

eess.IV20234 cited

Data efficient deep learning for medical image analysis: A survey

Suruchi Kumari, Pravendra Singh

The rapid evolution of deep learning has significantly advanced the field of medical image analysis. However, despite these achievements, the further enhancement of deep learning m…

cs.RO2023

Improving Trajectory Prediction in Dynamic Multi-Agent Environment by Dropping Waypoints

Pranav Singh Chib, Pravendra Singh

The inherently diverse and uncertain nature of trajectories presents a formidable challenge in accurately modeling them. Motion prediction systems must effectively learn spatial an…

eess.IV20231 cited

Deep learning for unsupervised domain adaptation in medical imaging: Recent advancements and future perspectives

Suruchi Kumari, Pravendra Singh

Deep learning has demonstrated remarkable performance across various tasks in medical imaging. However, these approaches primarily focus on supervised learning, assuming that the t…

cs.CV2021

DILF-EN framework for Class-Incremental Learning

Mohammed Asad Karim, Indu Joshi, Pratik Mazumder +1

Deep learning models suffer from catastrophic forgetting of the classes in the older phases as they get trained on the classes introduced in the new phase in the class-incremental…