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Our approach efficiently detects objects in an image while simultaneously generating a high-quality segmentation mask for each instance.
#2 best model for Multi-Human Parsing on MHP v1.0
We investigate conditional adversarial networks as a general-purpose solution to image-to-image translation problems.
Nuclear segmentation and classification within Haematoxylin & Eosin stained histology images is a fundamental prerequisite in the digital pathology work-flow.