Debesh Jha
Computer Vision and Pattern Recognition · 2019–2021
A researcher in the Science corpus: 5 papers; trusts 75 researchers and is trusted by 13 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 69 citations into it; #9,345 of 21,575 by trust here, #8,205 by citations
- Oncology — 45 citations into it; #585 of 1,698 by trust here, #867 by citations
- Artificial Intelligence — 33 citations into it
- Model Architectures — 16 citations into it
- Radiology, Nuclear Medicine and Imaging — 11 citations into it; #2,604 of 3,265 by trust here, #1,399 by citations
- Media Technology — 10 citations into it
- Ocean Engineering — 6 citations into it
Whom Debesh Jha trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jorge Bernal
- Kaiming He
- Liang-Chieh Chen
- Zhengxin Zhang
- Olaf Ronneberger
- F. Sánchez
- X. Zhang
- Geoffrey E. Hinton
- Alex Krizhevsky
- Jia Deng
Who trusts Debesh Jha overall
- Md Mostafijur Rahman
- Qing Xu
- Xiaoqi Zhao
- Taehun Kim
- Yundong Zhang
- Bingzhi Chen
- Tao Zhou
- Ailiang Lin
- B. Dong
- JunChao Wei
Papers from Debesh Jha's perspective
Ordered by how strongly the researchers Debesh Jha trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Going deeper with convolutions
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- A Comprehensive Study on Colorectal Polyp Segmentation With ResUNet++, Conditional Random Field and Test-Time Augmentation (2021) — 307 citations
- DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation (2020) — 819 citations
- HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy (2019) — 566 citations
- Kvasir-SEG: A Segmented Polyp Dataset (2019) — 1,927 citations
- ResUNet++: An Advanced Architecture for Medical Image Segmentation (2019) — 1,345 citations