AI RESEARCH
A Resource-Efficient Hybrid CNN-LSTM network for image-based bean leaf disease classification
arXiv CS.CV
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ArXi:2604.13835v1 Announce Type: new Accurate and resource-efficient automated diagnosis is a cornerstone of modern agricultural expert systems. While Convolutional Neural Networks (CNNs) have established benchmarks in plant pathology, their ability to capture long-range spatial dependencies is often limited by standard pooling layers, and their high memory footprint hinders deployment on portable devices. This paper proposes a lightweight hybrid CNN-LSTM system for bean leaf disease classification.