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Deep learning model efficiently detects banana beetle damage

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a lightweight deep learning framework using the YOLOv8n model to detect visible surface damage on bananas caused by the Basilepta subcostata beetle. This approach aims to provide a more objective and scalable alternative to manual inspection, which can reduce market value. The model was trained on a custom dataset of over 2,400 images from Bangladesh, achieving an F1-score of 77.67% and an [email protected] of 87.04%. The YOLOv8n model is noted for its small checkpoint size and efficient inference time on hardware like the NVIDIA Tesla T4. AI

IMPACT This research demonstrates a practical application of lightweight deep learning models for agricultural quality control, potentially improving efficiency and objectivity in produce inspection.

RANK_REASON Academic paper detailing a new deep learning approach for a specific detection task. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Deep learning model efficiently detects banana beetle damage

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Academic paper detailing a new deep learning approach for a specific detection task. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Md. Mehedi Hasan Naeem, Ishtiyak Ahmmad Araf, Md. Arefin Haque Mahir, Tushar Kanti Saha ·

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

    arXiv:2610.23661v1 Announce Type: cross 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…

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