ItemConference Paper

MCCLDP: Multi Class Cotton Leaf Diseases Prediction and Classification using Deep Learning Model

Title
MCCLDP: Multi Class Cotton Leaf Diseases Prediction and Classification using Deep Learning Model
Creator
Prasad, Kokkula Shiva; Balaram, Ambily; Rajender, Nagunuri; Sudheer, P.; Yerram, Sneha; Begum, Sumayyam
Description
Cotton plant disease detection is critical for sustainable agriculture and reducing crop losses. This paper proposes a novel Multi-Stream Attention-Guided Hybrid CNN (MAH-CNN) for accurate classification of cotton leaf diseases. The model leverages pre-trained ResNet152v2 and DenseNet-121 backbones for hierarchical feature extraction, complemented by a shallow CNN for localized texture analysis. A spatial attention mechanism enhances focus on disease-relevant regions, mitigating background noise. Features from the global and local streams are fused and passed through a lightweight classification head. The model achieves superior performance in terms of accuracy 97.32%, F1 score 98%, and specificity 100% on benchmark datasets which are available in open access, outperforming existing state-of-the-art methods. The integration of Grad-CAM provides interpretability, fostering trust in automated disease detection systems. 2025 IEEE.
Source
APCI 2025 - 2025 International Conference on Advancements in Power, Communication and Intelligent Systems;
Date
01-01-2025
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
Attention Mechanism; Classification Accuracy, Explainable AI; CNN; Cotton Leaf Disease Detection; DenseNet-121; Grad-CAM; Hybrid Feature Fusion; ResNet152v2; Transfer Learning
Coverage
Prasad K.S., Nalla Malla Reddy Engineering College, Department of ECE, Hyderabad, India; Balaram A., Christ University (Deemed to be University), Kengeri Campus, Department of CSE, Banglore, India; Rajender N., Kakatiya Institute of Tech and Science, Department of IT, Waranagal, India; Sudheer P., CVR College of Engineering, Department of CSE (AIML), Hyderabad, India; Yerram S., Nalla Malla Reddy Engineering College, Department of CSE, Hyderabad, India; Begum S., Lords Institute of Engg and Tech, Department of IT, Hyderabad, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-833152387-9;
Format
online
Language
English
Type
Conference paper

Citation

Prasad, Kokkula Shiva; Balaram, Ambily; Rajender, Nagunuri; Sudheer, P.; Yerram, Sneha; Begum, Sumayyam, “MCCLDP: Multi Class Cotton Leaf Diseases Prediction and Classification using Deep Learning Model,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 17, 2026, https://archives.christuniversity.in/items/show/25761.

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