Cocoa Ripeness Classification Using Vision Transformer

Cocoa Ripeness Classification Using Vision Transformer

The quality of manual methods for assessing the ripeness of cocoa pods is subjective and varies from one person to another because of the intense labor required and variation of light and background conditions within the field. This research implemented an automated classification approach for coco...

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Bibliographic Details
Main Authors: Febryanti Sthevanie, Untari Novia Wisesty, Gia Septiana Wulandari, Kurniawan Nur Ramadhani
Format: Article
Language:English
Published: Yayasan Pendidikan Riset dan Pengembangan Intelektual (YRPI) 2025-06-01
Series:Journal of Applied Engineering and Technological Science
Subjects:
Cocoa Ripeness Classification
Vision Transformer
Shifted Patch Tokenization
Locality Self Attention
Agricultural Computer Vision
Online Access:http://journal.yrpipku.com/index.php/jaets/article/view/6663
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