Automating parasite egg detection: insights from the first AI-KFM challenge.

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Bibliographic Details
Title: Automating parasite egg detection: insights from the first AI-KFM challenge.
Authors: Capuozzo S; Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy., Marrone S; Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy., Gravina M; Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy., Cringoli G; Department of Veterinary Medicine and Animal Productions, University of Naples Federico II, Naples, Italy., Rinaldi L; Department of Veterinary Medicine and Animal Productions, University of Naples Federico II, Naples, Italy., Maurelli MP; Department of Veterinary Medicine and Animal Productions, University of Naples Federico II, Naples, Italy., Bosco A; Department of Veterinary Medicine and Animal Productions, University of Naples Federico II, Naples, Italy., Orrù G; Department of Electrical and Electronic Engineering, University of Cagliari, Cagliari, Italy., Marcialis GL; Department of Electrical and Electronic Engineering, University of Cagliari, Cagliari, Italy., Ghiani L; Department of Biomedical Sciences, University of Sassari, Sassari, Italy., Bini S; Department of Information Engineering, Electrical Engineering and Applied Mathematics, University of Salerno, Salerno, Italy., Saggese A; Department of Information Engineering, Electrical Engineering and Applied Mathematics, University of Salerno, Salerno, Italy., Vento M; Department of Information Engineering, Electrical Engineering and Applied Mathematics, University of Salerno, Salerno, Italy., Sansone C; Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy.
Source: Frontiers in artificial intelligence [Front Artif Intell] 2024 Aug 29; Vol. 7, pp. 1325219. Date of Electronic Publication: 2024 Aug 29 (Print Publication: 2024).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Media SA Country of Publication: Switzerland NLM ID: 101770551 Publication Model: eCollection Cited Medium: Internet ISSN: 2624-8212 (Electronic) Linking ISSN: 26248212 NLM ISO Abbreviation: Front Artif Intell Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2624-8212
DOI:10.3389/frai.2024.1325219