Crop Row Detection

Crop row detection aims to automatically identify crop rows in agricultural fields using image data, primarily to enable autonomous navigation for robots and precision agriculture tasks like weed management. Current research focuses on developing robust algorithms, often employing deep learning models, that can handle diverse field conditions such as varying light levels, weed density, crop types, and growth stages, sometimes incorporating multispectral imagery or LiDAR data for improved accuracy. These advancements are crucial for improving the efficiency and precision of agricultural operations, leading to optimized resource use and increased crop yields.