Machine learningObject detection / segmentation

Mask R-CNN: Instance Segmentation with Pixel-Level Masks

Mask R-CNN is a deep learning framework for instance segmentation introduced by Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick at Facebook AI Research (FAIR) in 2017. It extends Faster R-CNN by adding a parallel branch that predicts a binary pixel-level mask for each detected object instance, enabling simultaneous object detection, classification, and fine-grained segmentation in a single forward pass.

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Sources

  1. He, K., Gkioxari, G., Dollár, P., & Girshick, R. (2017). Mask R-CNN. IEEE International Conference on Computer Vision (ICCV), 2980–2988. DOI: 10.1109/ICCV.2017.322

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Referenced by

ScholarGateMask R-CNN (Mask R-CNN (Instance Segmentation)). Retrieved 2026-06-04 from https://scholargate.app/tr/deep-learning/mask-rcnn