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GourNet CNN model achieves 97% accuracy in mango leaf disease detection

作者 PulseAugur 编辑部 · [2 个来源] ·

Researchers have developed GourNet, a Convolutional Neural Network model designed to detect diseases in mango leaves. Trained on the MangoLeafBD dataset, which includes eight classes (seven diseases and one healthy), GourNet achieved a 97% classification accuracy. The model utilizes data augmentation and preprocessing techniques, and its source code has been made publicly available. AI

影响 Potential for improved crop management and yield through early disease detection in mango cultivation.

排序理由 Academic paper detailing a new CNN model for a specific agricultural task.

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

GourNet CNN model achieves 97% accuracy in mango leaf disease detection

报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Ekram Alam, Jaydip Sanyal, Akhil Kumar Das, Arijit Bhattacharya, Farhana Sultana ·

    GourNet: A CNN-Based Model for Mango Leaf Disease Detection

    arXiv:2604.27764v1 Announce Type: new Abstract: Mango cultivation is crucial in the agricultural sector, significantly contributing to economic development and food security. However, diseases affecting mango leaves can significantly reduce both the production and overall fruit g…

  2. arXiv cs.CV TIER_1 English(EN) · Farhana Sultana ·

    GourNet: A CNN-Based Model for Mango Leaf Disease Detection

    Mango cultivation is crucial in the agricultural sector, significantly contributing to economic development and food security. However, diseases affecting mango leaves can significantly reduce both the production and overall fruit grade. Detecting leaf diseases at an early stage …

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