About this document
Medical Video Classification Redefined by samyakssanghvi is a document available to read on EtoBox.
The document presents a novel approach to medical video classification by reformulating it as a set-prediction problem rather than a sequence-prediction problem, addressing issues with traditional frame-wise classification methods. This method leverages multi-instance learning and 2-D neural networks to improve computational efficiency and accuracy while avoiding the biases associated with frame-level annotations. The approach has shown superior performance on various medical imaging tasks, including gallbl
- Author
- samyakssanghvi
- Language
- EN