Identification of veterinary and medically important blood parasites using contrastive loss-based self-supervised learning

Identification of veterinary and medically important blood parasites using contrastive loss-based self-supervised learning

Background and Aim: Zoonotic diseases caused by various blood parasites are important public health concerns that impact animals and humans worldwide. The traditional method of microscopic examination for parasite diagnosis is labor-intensive, time-consuming, and prone to variability among observers...

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Main Authors: Supasuta Busayakanon, Morakot Kaewthamasorn, Natchapon Pinetsuksai, Teerawat Tongloy, Santhad Chuwongin, Siridech Boonsang, Veerayuth Kittichai
Format: Article
Language:English
Published: Veterinary World 2024-11-01
Series:Veterinary World
Subjects:
bootstrap your own latent
fractioned data
microscopic image
pre-trained
self-supervised learning
zoonotic disease
Online Access:https://www.veterinaryworld.org/Vol.17/November-2024/22.pdf
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https://www.veterinaryworld.org/Vol.17/November-2024/22.pdf

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