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An Efficient Approach to Beetle Damage Detection of Banana Using Deep Learning

Paper recorded by Signals 4 on 2026-10-16 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-16 on arXiv · recorded by Signals 4 on 2026-10-19

Category: cs.CV · 计算机视觉 · first seen 2026-10-19

Abstract

Visible surface damage of banana fruits by Basilepta subcostata (the banana fruit scarring beetle) can reduce their market value. Here, manual inspection of Banana fruits is subjective and difficult to scale. This study presents a lightweight framework based on YOLOv8n deep learning model for locating individual bananas and classifying their visible surface condition as healthy or unhealthy. The t

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#243 most recent of 756 cs.CV papers we have recorded · ↑ newer: PCDFusion: Proposal-Context-Detail Bayesian Rendering for Infrared-Vis · ↓ older: FlexPart: Text-Controlled Semantics-Aware 3D Part Segmentation at Flex
Cite this page: An Efficient Approach to Beetle Damage Detection of Banana Using Deep Learning: the #243 most recent of 756 cs.CV papers we have recorded (as of 2026-10-16). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/an-efficient-approach-to-beetle-damage-detection-of-banana-using-deep-learning.html
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