The MS COCO (Microsoft Common Objects in Context) dataset is a large-scale object detection, segmentation, key-point detection, and captioning dataset. The dataset consists of 328K images.
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HyperKvasir dataset contains 110,079 images and 374 videos where it captures anatomical landmarks and pathological and normal findings. A total of around 1 million images and video frames altogether.
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A challenge that consists of three tasks, each targeting a different requirement for in-clinic use. The first task involves classifying images from the GI tract into 23 distinct classes. The second task focuses on efficiant classification measured by the amount of time spent processing each image. The last task relates to automatcially segmenting polyps.
2 PAPERS • 1 BENCHMARK