Vidhiwar Singh Rathour Source Confirmed
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
University of Arkansas at Fayetteville
unknown
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Biography and Research Information
OverviewAI-generated summary
Vidhiwar Singh Rathour's research focuses on the application of deep learning techniques, particularly deep reinforcement learning, to computer vision tasks and medical image analysis. His work includes developing and evaluating deep neural network architectures for medical image segmentation, with a focus on invertible residual networks. Rathour has also investigated methods for benchmarking medical segmentation accuracy, proposing novel metrics like the Roughness Index and Roughness Distance. His publications include a comprehensive survey on deep reinforcement learning in computer vision and studies on classifying ECG arrhythmias using multi-module recurrent convolutional neural networks. Rathour has collaborated with researchers at the University of Arkansas at Fayetteville, including Kashu Yamakazi and Khoa Luu, on multiple shared publications.
Metrics
- h-index: 4
- Publications: 8
- Citations: 286
Selected Publications
- Invertible residual network with regularization for effective volumetric segmentation (2022) DOI
- Deep reinforcement learning in computer vision: a comprehensive survey (2021) DOI
- Multi-module Recurrent Convolutional Neural Network with Transformer Encoder for ECG Arrhythmia Classification (2021) DOI
- Roughness Index and Roughness Distance for Benchmarking Medical Segmentation (2021) DOI
- Roughness Index and Roughness Distance for Benchmarking Medical Segmentation (2021) DOI
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