{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["15"],"submitter":["Uddin MS"],"funding":["King Saud University"],"pubmed_abstract":["Cauliflower cultivation plays a pivotal role in the Indian Subcontinent's winter cropping landscape, contributing significantly to both agricultural output, economy and public health. However, the susceptibility of cauliflower crops to various diseases poses a threat to productivity and quality. This paper presents a novel machine vision approach employing a modified YOLOv8 model called Cauli-Det for automatic classification and localization of cauliflower diseases. The proposed system utilizes images captured through smartphones and hand-held devices, employing a finetuned pre-trained YOLOv8 architecture for disease-affected region detection and extracting spatial features for disease localization and classification. Three common cauliflower diseases, namely 'Bacterial Soft Rot', 'Downey "],"journal":["Frontiers in plant science"],"pagination":["1373590"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11063243"],"repository":["biostudies-literature"],"pubmed_title":["Cauli-Det: enhancing cauliflower disease detection with modified YOLOv8."],"pmcid":["PMC11063243"],"pubmed_authors":["Mridha MF","Safran M","Che D","Prity AJ","Mazumder MKA","Alfarhood S","Uddin MS"],"additional_accession":[]},"is_claimable":false,"name":"Cauli-Det: enhancing cauliflower disease detection with modified YOLOv8.","description":"Cauliflower cultivation plays a pivotal role in the Indian Subcontinent's winter cropping landscape, contributing significantly to both agricultural output, economy and public health. However, the susceptibility of cauliflower crops to various diseases poses a threat to productivity and quality. This paper presents a novel machine vision approach employing a modified YOLOv8 model called Cauli-Det for automatic classification and localization of cauliflower diseases. The proposed system utilizes images captured through smartphones and hand-held devices, employing a finetuned pre-trained YOLOv8 architecture for disease-affected region detection and extracting spatial features for disease localization and classification. Three common cauliflower diseases, namely 'Bacterial Soft Rot', 'Downey ","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024","modification":"2026-03-27T16:37:02.765Z","creation":"2025-08-27T03:08:43.318Z"},"accession":"S-EPMC11063243","cross_references":{"pubmed":["38699536"],"doi":["10.3389/fpls.2024.1373590"]}}