Titlebook: Computer Vision and Machine Learning in Agriculture, Volume 3; Jagdish Chand Bansal,Mohammad Shorif Uddin Book 2023 The Editor(s) (if appl

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,A New Methodology to?Detect Plant Disease Using Reprojected Multispectral Images from?RGB Colour Sp importance, feasibility, and applicability of the proposed method to identify plant diseases with affordable limits. The research found that the proposed model able to improve 4.35% detection accuracy compare to RGB colour-based images using identical deep learning-based detection model. To do so,

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,Analysis of?the?Performance of?YOLO Models for?Tomato Plant Diseases Identification,ction scores on detection accuracy, precision, recall and F-1 score. However, YOLO-5 tiny performs better in terms of detection time but comprises detection accuracy. In this study, a publicly available data set name . has been used.

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,Strawberries Maturity Level Detection Using Convolutional Neural Network (CNN) and?Ensemble Method,oposed based on SqueezeNet, GoogleNet, and VGG-16. Based on the considered performance matrices, SqueezeNet is recommended as the most effective model among all the classifiers and networks for detecting and classifying the maturity levels of strawberries.

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Leveraging Computer Vision for Precision Viticulture, automation, posing new challenges and objectives that have not yet been explored. This work intends to deliver a complete guide of the current status of computer vision in viticulture, covering all management practices, such as pruning, binding, shoot thinning, weeding, spraying, leaf thinning, top

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2524-7565 nd overall automation through robots and drones. The topics covered in the current volume, along with the previous volumes, are comprehensive literature for both beginners and experienced in this domain..978-981-99-3756-1978-981-99-3754-7Series ISSN 2524-7565 Series E-ISSN 2524-7573