• CNNs were designed to map image data to an output variable.• CNN’s have been used for plant image analysis since the early days of their evolution • CNN’s consist of convolutional layers, which are sets of image filters convoluted to images or feature maps • Feature maps are extracted through convolution and other processing layers repetitively and the network eventually outputs a label indicating an estimated class CNN’s have been used for plant image analysis since the early days of their evolution. The use of CNNs in plant disease classification has achieved excellent results in recent years. It consists of convolutional layers, which are sets of image filters convoluted to images or feature maps Problem statement: Leaf disease analysis using CNN Need Analysis: Leaf disease is an ongoing challenge for smallholder farmers, which threatens income and food security. The recent revolution in smartphone penetration and computer vision models has created an opportunity for image classification in agriculture. Convolutional Neural Networks (CNNs) are considered state-of-the-art in image recognition and offer the ability to provide a prompt and definite diagnosis.
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