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Data · dataset · 2023

Implementation of ['YOLO-OB: An improved anchor-free real-time multi-scale colon polyp detector in colonoscopy']

Listed in Teesside University Research Data Repository

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.

Description

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.

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Where it is published

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Teesside University Research Data Repositoryoai:data.mendeley.com/xj3x7vmsdg.15 h agoJSON v1
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