Crop Field

Crop field analysis is crucial for optimizing agricultural practices and resource management, focusing on accurate and efficient identification of field boundaries and features within those boundaries. Current research heavily utilizes deep learning, employing architectures like U-Net and YOLOv5, along with techniques such as transfer learning and semi-supervised learning, to analyze high-resolution satellite and drone imagery for tasks ranging from crop field segmentation and weed detection to assessing crop health and yield prediction. These advancements enable precision agriculture, facilitating site-specific interventions like targeted pesticide application and ultimately improving crop productivity and sustainability.