RGB Dataset

RGB datasets are collections of images captured in the red, green, and blue color channels, serving as foundational data for various computer vision tasks. Current research focuses on developing and utilizing these datasets for applications ranging from flood detection and plant disease identification to object detection in challenging conditions like low light or small object sizes, employing deep learning models such as U-Net and YOLOv8, along with advancements in image translation techniques. The availability of high-quality, labeled RGB datasets, often augmented with other data modalities like NIR or thermal imagery, is crucial for advancing the accuracy and generalizability of computer vision algorithms across diverse real-world applications.