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Deep Learning Techniques for Smart Agriculture Applications
Abstract
With an emphasis on the rapid and accurate diagnosis of plant and fruit diseases, researchers have been looking into sustainable agriculture utilizing cutting-edge deep learning techniques. The objective is to show how effective deep learning algorithms can revolutionize the agricultural industry. Automated illness detection is the main area of focus, where advances in image processing and computer vision techniques enable precise and quick identification while lowering labor requirements and associated costs. In order to identify plant and fruit diseases in a sustainable manner, this project intends to explore the possibilities of deep learning algorithms in detecting diseases from the leaves of agricultural plants using pre-trained deep convolutional neural network. This book chapter provides informative information on the use of deep learning in smart agriculture and a significant resource for researchers, professionals, and students interested in sustainable farming and intelligent agricultural systems.
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