Agricultural Domain
Agricultural research is rapidly advancing through the integration of artificial intelligence and robotics, aiming to optimize farming practices, increase yields, and enhance sustainability. Current efforts focus on developing and deploying computer vision models (like YOLO variants and neural radiance fields), machine learning algorithms for tasks such as disease detection, precision irrigation, and crop yield prediction, and integrating these technologies with autonomous robots and drones. These advancements hold significant promise for improving efficiency, reducing resource waste, and addressing global food security challenges by enabling more precise and data-driven farming methods.
Papers
A comprehensive review of 3D convolutional neural network-based classification techniques of diseased and defective crops using non-UAV-based hyperspectral images
Nooshin Noshiri, Michael A. Beck, Christopher P. Bidinosti, Christopher J. Henry
Web of Things and Trends in Agriculture: A Systematic Literature Review
Muhammad Shoaib Farooq, Shamyla Riaz, Atif Alvi