2026-10-16T01:28:44Z https://data.mendeley.com/oai

oai:data.mendeley.com/xj3x7vmsdg.1 2023-08-29T13:41:41Z

yan, sean Implementation of ['YOLO-OB: An improved anchor-free real-time multi-scale colon polyp detector in colonoscopy'] Mendeley Data This repo is the implementation of ['YOLO-OB: An improved anchor-free real-time multi-scale colon polyp detector in colonoscopy'] The deep learning-based object detection algorithm is currently one of the most effective methods for improving polyp detection during colonoscopy. This repository proposes a new model called YOLO-OB based on YOLOv3. It improves network's feature fusion capacity by adopting the Spatial Pyramid Pooling (SPP) and the Bi-directional Feature Pyramid Network (BiFPN) modules. It also employs the ObjectBox detection head, which uses a center-based anchor-free box regression strategy that can detect polyps of different sizes on feature maps of any scale. Object Detection Algorithm Dataset doi:10.17632/xj3x7vmsdg.1 oai:data.mendeley.com/xj3x7vmsdg.1 Creative Commons Attribution 4.0 International http://creativecommons.org/licenses/by/4.0 https://data.mendeley.com/datasets/xj3x7vmsdg 2023-08-29T13:41:41Z