The integration of computer vision into agriculture addresses critical societal challenges, including food security and environmental sustainability. By enabling precise crop monitoring, early disease detection, and resource-efficient farming practices, it helps optimize food production to meet the needs of a growing global population. This technology also reduces waste and minimizes environmental impact, contributing to more sustainable agricultural systems. Furthermore, it supports farmers by improving decision-making and enhancing productivity in the face of climate change and resource limitations. Overall, computer vision plays a key role in creating resilient food systems essential for a sustainable future. Computer Vision Techniques for Agricultural Advancements explores the dynamic intersection of computer vision, artificial intelligence (AI) and agriculture, offering a comprehensive overview of the latest trends, challenges, and opportunities in this rapidly evolving field. Through a series of in-depth chapters, it examines various applications of computer vision across different stages of agricultural production and management, showcasing its impact on productivity, efficiency, and sustainability. Covering topics such as AI, food safety, and yield prediction, this book is an excellent resource for researchers, academicians, agricultural engineers and technologists, agribusiness professionals, graduate and postgraduate students, technology developers, policymakers, consultants, educators, and more.