405 citations · 1.1k across the 81 of their papers we have counts for
5 papers · 2 filters
A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time Augmentation
Debesh Jha, Pia H. Smedsrud, Dag Johansen +4
Colonoscopy is considered the gold standard for detection of colorectal cancer and its precursors. Existing examination methods are, however, hampered by high overall miss-rate, an…
Meta-learning with implicit gradients in a few-shot setting for medical image segmentation
Rabindra Khadga, Debesh Jha, Steven Hicks +4
Widely used traditional supervised deep learning methods require a large number of training samples but often fail to generalize on unseen datasets. Therefore, a more general appli…
Progressively Normalized Self-Attention Network for Video Polyp Segmentation
Ge-Peng Ji, Yu-Cheng Chou, Deng-Ping Fan +4
Existing video polyp segmentation (VPS) models typically employ convolutional neural networks (CNNs) to extract features. However, due to their limited receptive fields, CNNs can n…
FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation
Nikhil Kumar Tomar, Debesh Jha, Michael A. Riegler +5
The increase of available large clinical and experimental datasets has contributed to a substantial amount of important contributions in the area of biomedical image analysis. Imag…
LightLayers: Parameter Efficient Dense and Convolutional Layers for Image Classification
Debesh Jha, Anis Yazidi, Michael A. Riegler +3
Deep Neural Networks (DNNs) have become the de-facto standard in computer vision, as well as in many other pattern recognition tasks. A key drawback of DNNs is that the training ph…