A YOLOv8n model pre-trained on a fruit and vegetable detection dataset achieved 95.1% F1 on polyp detection, outperforming COCO-pre-trained and scratch-trained models.
kCBAC-Net: Deeply supervised complete bipar- tite networks with asymmetric convolutions for medical image segmentation,
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Exploring Transfer Learning for Deep Learning Polyp Detection in Colonoscopy Images Using YOLOv8
A YOLOv8n model pre-trained on a fruit and vegetable detection dataset achieved 95.1% F1 on polyp detection, outperforming COCO-pre-trained and scratch-trained models.