most citedDomain-Adaptive Learning: Unsupervised Adaptation for Histology Images with Improved Loss Function Combination

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cs.CV2023

Combining Datasets with Different Label Sets for Improved Nucleus Segmentation and Classification

Amruta Parulekar, Utkarsh Kanwat, Ravi Kant Gupta +5

Segmentation and classification of cell nuclei in histopathology images using deep neural networks (DNNs) can save pathologists' time for diagnosing various diseases, including can…

cs.CV2023★ 1 cited

Domain-Adaptive Learning: Unsupervised Adaptation for Histology Images with Improved Loss Function Combination

Ravi Kant Gupta, Shounak Das, Amit Sethi

This paper presents a novel approach for unsupervised domain adaptation (UDA) targeting H&E stained histology images. Existing adversarial domain adaptation methods may not effecti…