Eosinophil Detection with Modified YOLOv3 Model in Large Pathology Image

Author:

Wang Xinyue1,Che Yonggang1,Jiang Nan2,Chen Weijian2,Lan Long1

Affiliation:

1. National University of Defense Technology,State Key Laboratory of High Performance Computing College of Computer,Changsha,China

2. Hunan Children's Hospital,Department of Pathology,Changsha,China

Funder

Health

Publisher

IEEE

Reference16 articles.

1. You only look once: Unified, real-time object detection[C];redmon;IEEE Conference on Computer Vision and Pattern Recognition,2016

2. YOLO9000: Better, Faster, Stronger

3. Receptive field block net for accurate and fast object detection[C];liu;European Conference on Computer Vision,2018

4. Deep Residual Learning for Image Recognition

5. Microsoft COCO: Common Objects in Context[C];lin;European Conference on Computer Vision,2014

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1. The Framework for Training and Validation of Healthcare System using Accurate Classifier Model;2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE);2024-05-14

2. Eosinophils instance object segmentation on whole slide imaging using multi-label circle representation;Medical Imaging 2024: Digital and Computational Pathology;2024-04-03

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