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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Auteurs principaux:	Supasuta Busayakanon, Morakot Kaewthamasorn, Natchapon Pinetsuksai, Teerawat Tongloy, Santhad Chuwongin, Siridech Boonsang, Veerayuth Kittichai
Format:	Artigo
Langue:	Inglês
Publié:	Veterinary World 2024-11-01
Collection:	Veterinary World
Sujets:	bootstrap your own latent fractioned data microscopic image pre-trained self-supervised learning zoonotic disease
Accès en ligne:	https://www.veterinaryworld.org/Vol.17/November-2024/22.pdf
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