TAPe: Computer Vision AI Reaches 98% Accuracy
TAPe continues its diary of COCO experiments with a new step: 98% accuracy on a two-percent subset, fewer false positives, and first results with rectangular bounding boxes. The authors also found a workable balance between background and objects, cut the number of misses to 30 on the test set, and checked how many "glimpses" the model actually needs for detection.
AI-processed from Habr AI; edited by Hamidun News
TAPe, a computer vision AI project, is continuing its series of open experiments on COCO and reports a new local result: accuracy rose to roughly 98% on a two-percent subset of the dataset.
How did TAPe improve accuracy in computer vision?
The team moved from finding object centers (centroids) to full box detection and reduced the number of false positives, reaching 98% accuracy on the COCO dataset.
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