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Deep Learning Models Achieve High Accuracy in Plant Disease Classification

By PulseAugur Editorial · [4 sources] ·

Researchers have developed advanced deep learning frameworks for classifying plant diseases from leaf images, achieving high accuracy rates. One study focused on lemon leaf disease, utilizing ensemble models like InceptionV3 and MobileNetV2, reaching 99.27% accuracy with adversarial training for robustness. Another framework, CottonLeafVision, employed models such as DenseNet201, InceptionV3, and VGG19 to classify cotton leaf diseases, with DenseNet201 achieving 98% accuracy. A hybrid approach combining ResNet-50 with Vision Transformers also demonstrated strong performance, reaching 98.58% accuracy for multi-class plant disease identification, with interpretability techniques like Grad-CAM used across these studies to highlight disease-relevant regions. AI

IMPACT These frameworks offer improved accuracy and interpretability for precision agriculture, aiding in early disease detection and management.

RANK_REASON Multiple research papers published on arXiv detailing new deep learning frameworks for plant disease classification.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 4 sources. How we write summaries →

COVERAGE [4]

  1. arXiv cs.AI TIER_1 English(EN) · Shayan Abrar, Sudeepta Mandal, Abdul Awal Yasir, Sonjoy Bhattacharjee, Sadman Haque Bhuiyan, Samanta Ghosh, Rafi Ahamed ·

    An Ensemble Deep Learning Approach for Reliable and Scalable Lemon Leaf Disease Classification

    arXiv:2606.14871v1 Announce Type: cross Abstract: Early detection of plant diseases is crucial to plants and for the farmers. Plant diseases reduce fruit yield and quality, and plants are more susceptible to other stresses when they are infected. The lemon leaf disease dataset co…

  2. arXiv cs.AI TIER_1 English(EN) · Rafi Ahamed, Md. Abir Rahman, Tasnia Tarannum Roza, Munaia Jannat Easha, Md. Asif Khan, Sudeepta Mandal ·

    CottonLeafVision: An Explainable and Robust Deep Learning Framework for Cotton Leaf Disease Classification

    arXiv:2606.14686v1 Announce Type: cross Abstract: Globally, cotton is a highly economically beneficial crop, as the textile industry heavily depends on it. So, the precise identification and detection of cotton leaf disease is crucial for economic stability. The development goal …

  3. arXiv cs.CV TIER_1 English(EN) · Hasibul Islam Sufi, Ridam Roy, Shayla Alam Setu, Mahimul Islam Nadim ·

    Enhancing Precision Agriculture with a Hybrid Deep Learning Framework for Multi-Class Plant Disease Classification and Interpretability

    arXiv:2606.15282v1 Announce Type: new Abstract: This study proposes an overall deep learning architecture for multi-class classification of plant diseases from high-resolution leaf imagery, with a particular interest in investigating the behavior of ResNet-50 and a hybrid ResNet …

  4. arXiv cs.CV TIER_1 English(EN) · Sudeepta Mandal ·

    CottonLeafVision: An Explainable and Robust Deep Learning Framework for Cotton Leaf Disease Classification

    Globally, cotton is a highly economically beneficial crop, as the textile industry heavily depends on it. So, the precise identification and detection of cotton leaf disease is crucial for economic stability. The development goal of "CottonLeafVision" is to accurately classify an…

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