Development of Self-Supervised Learning with Dinov2-Distilled Models for Parasite Classification in Screening-Reference-Cited by-同舟云学术

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Development of Self-Supervised Learning with Dinov2-Distilled Models for Parasite Classification in Screening

Published:2023-10-26 Issue: Volume: Page:
ISSN:
Container-title:2023 15th International Conference on Information Technology and Electrical Engineering (ICITEE)
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Author:

Pinetsuksai Natchapon¹,Kittichai Veerayuth²,Jomtarak Rangsan³,Jaksukam Komgrit¹,Tongloy Teerawat¹,Boonsang Siridech⁴,Chuwongin Santhad¹

Affiliation:

1. College of Advanced Manufacturing Innovation, King Mongkut's Institute of Technology Ladkrabang,Bangkok,Thailand

2. King Mongkut's Institute of Technology Ladkrabang,Faculty of Medicine,Bangkok,Thailand

3. Suan Dusit University,Faculty of Science and Technology,Bangkok,Thailand

4. School of Engineering King Mongkut's Institute of Technology Ladkrabang,Department of Electrical Engineering,Bangkok,Thailand

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10317623/10317639/10317719.pdf?arnumber=10317719

Reference18 articles.

1. Superior Automatic Screening for Human Helminthic Ova by Using Self-supervised Learning Approach-Based Object Classification

2. Parasitic Egg Detection and Classification in Microscopic Images;palasuwan;IEEE Dataport,2022

3. Multi-Class Confusion Matrix Reduction method and its application on Net Promoter Score classification problem

4. Automatic recognition of parasitic products in stool examination using object detection approach

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