Jan 22, 2021 · We propose FocAnnot, a patch-wise active learning method, to reduce duplicate annotation and save cost in the intensive cell image segmentation ...
In this study, we present a patch-wise active learning method, namely FocAnnot (focal annotation), to avoid such worthless annotation. The main idea is to group ...
May 2, 2024 · Cell image segmentation is usually implemented using fully supervised deep learning methods, which heavily rely on extensive annotated training ...
Missing: FocAnnot: Patch- Wise
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In this study, we present a patch-wise active learning method, namely FocAnnot (focal annotation), to avoid such worthless annotation. The main idea is to group ...
Our approach introduces a pseudo-label-based filter addressing excessive blank patches in medical abnormalities segmentation tasks, e.g., lesions, and tumors, ...
• Discrepancy-based Active Learning for Weakly Supervised Bleeding Segmentation ... • End-to-End Segmentation of Medical Images via Patch-wise Polygons Prediction.
Active deep learning with fisher information for patch-wise semantic segmentation ... Interactive cell segmentation based on active and semi-supervised learning.
Missing: FocAnnot: | Show results with:FocAnnot:
The review covers automatic segmentation of images by means of deep learning approaches in the area of medical imaging. Current developments in machine ...
Missing: FocAnnot: | Show results with:FocAnnot:
Sep 20, 2018 · In this paper, we presented active learning (AL) algorithms based on Fisher information (FI) for patch-wise image segmentation using CNNs.
Missing: FocAnnot: Intensive Cell