…The last task relates to automatcially segmenting polyps. Please cite "The EndoTect 2020 Challenge: Evaluation andComparison of Classification, Segmentation and Inference Time for Endoscopy" if you use the dataset.
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…There are two common metrics: Detection AUROC and Segmentation (or pixelwise) AUROC Detection (or, classification) methods output single float (anomaly score) per input test image. Segmentation methods output anomaly probability for each pixel. "To assess segmentation performance, we evaluate the relative per-region overlap of the segmentation with the ground truth. We define the true positive rate as the percentage of pixels that were correctly classified as anomalous" [1] Later segmentation metric was improved to balance regions with small and large area, see PRO-AUC
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…The dataset can be used for lesion recognition tasks such as lesion segmentation, lesion detection and lesion classification.
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…All images have an associated ground truth annotation of breed, head ROI, and pixel level trimap segmentation. Also available on Academic torrent, Link is here
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…It contains classification labels as well as point-level and segmentation labels to have a more comprehensive fish analysis benchmark.
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…GeoDanmark with a variable Ground Sample Distance (GSD) between 10 cm and 15 cm, all sampled between March 1st and May 1st during 2021, containing 23,417 hand labelled images for classification and 880 segmentation
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…To simplify the problem of hand segmentation, subjects wore fluorescent-colored gloves. These substantially simplify the problem of recognizing the position of the hand and performing its segmentation, and remove all issues associated to skin color variations, while fully retaining the difficulty
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…A subset of 1.9M includes diverse annotations types. 15,851,536 boxes on 600 classes 2,785,498 instance segmentations on 350 classes 3,284,280 relationship annotations on 1,466 relationships 675,155
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…Image segmentation. 7. Image retrieval
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…Bean images obtained by computer vision system were subjected to segmentation and feature extraction stages, and a total of 16 features; 12 dimensions and 4 shape forms, were obtained from the grains.
…The dataset can be used for multi-label based image classification, multi-label based image retrieval, and image segmentation.
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