Applications of CNN in leaf diseases: A critical survey

Crop diseases can significantly impact crop yield and overall productivity, posing challenges for farmers in increasing output market prices. Early detection of these is crucial preventing further spread reducing their impact. To overcome this, researchers have utilized image processing technology, including deep learning techniques such as convolutional neural networks (CNNs), to detect diseases. In this critical survey, we provide a comprehensive review recent studies developments the use CNNs identifying leaf agricultural plants. We discuss benefits drawbacks different methods disease diagnosis management agriculture. Our research highlights potential advance field development. also analyze factors affecting outcomes each technique, accuracy, precision. study emphasizes need development optimize applications, particularly improving productivity.