Shiva Paudel

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Shiva Paudel's research focuses on developing and applying advanced computational methods, particularly deep learning, for identification and analysis in agricultural and biological contexts. His work has explored the use of point cloud data and 3D imaging for non-invasive individual animal identification in livestock, aiming to provide alternatives to traditional methods like RFID. Paudel has also investigated the application of deep learning and imaging techniques for detecting myopathies in chicken fillets. His scholarship includes a historical perspective on animal identification methods, spanning from prehistoric times to the present. Paudel has co-authored publications with researchers at the University of Arkansas at Fayetteville, including Kristopher A. Bottoms, Dongyi Wang, Cengiz Koparan, and Jeyamkondan Subbiah.

Metrics

• h-index: 3
• Publications: 9
• Citations: 40