ICIP 2022 Challenge on Parasitic Egg Detection and Classification in Microscopic Images: Dataset, Methods and Results-Reference-Cited by-同舟云学术

ICIP 2022 Challenge on Parasitic Egg Detection and Classification in Microscopic Images: Dataset, Methods and Results

Published:2022-10-16 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Image Processing (ICIP)
language:
Short-container-title:

Author:

Anantrasirichai Nantheera¹,Chalidabhongse Thanarat H.²,Palasuwan Duangdao³,Naruenatthanaset Korranat²,Kobchaisawat Thananop²,Nunthanasup Nuntiporn³,Boonpeng Kanyarat³,Ma Xudong¹,Achim Alin¹

Affiliation:

1. University of Bristol,Visual Information Laboratory,UK

2. Chulalongkorn University,Department of Computer Engineering,Thailand

3. Chulalongkorn University,Oxidation in Red Cell Disorders Research Unit,Department of Clinical Microscopy,Thailand

Funder

Newton Fund

British Council

National Research Council of Thailand

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9897158/9897159/09897267.pdf?arnumber=9897267

Reference31 articles.

1. Detection of parasitic eggs from microscopy images and the emergence of a new dataset;mayo,2022

2. Faster R-CNN: Towards real-time object detection with region proposal networks;ren;Advances in neural information processing systems,2015

3. Parasitic egg detection and classification via multi-technique;wang,0

4. Parasitic egg detection and classification in microscopic images;palasuwan;IEEE Dataport,2022

5. CBNetV2: A Composite Backbone Network Architecture for Object Detection;liang,2021

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