Jan 12, 2024 · This paper demonstrates a self-supervised framework for learning voxel-wise coarse-to-fine representations tailored for dense downstream tasks.
May 26, 2024 · This paper demonstrates a self-supervised framework for learning voxel-wise coarse-to-fine representations tailored for dense downstream ...
This repository is the implementation of the paper 'Self-supervised Learning of Dense Hierarchical Representations for Medical Image Segmentation' submitted ...
Aug 25, 2024 · Medical Imaging. Conference Paper. Self-Supervised Learning of Dense Hierarchical Representations for Medical Image Segmentation. May 2024. DOI ...
We propose Pix2Rep, a self-supervised learning (SSL) approach for few-shot segmentation, that reduces the manual annotation burden by learning powerful pixel- ...
Missing: Hierarchical | Show results with:Hierarchical
May 27, 2024 · This paper presents a self-supervised learning approach for training dense hierarchical representations to improve medical image ...
Sep 13, 2024 · We propose Pix2Rep, a self-supervised learning (SSL) approach for few-shot segmentation, that reduces the manual annotation burden by learning ...
In this paper, we propose Hierarchical Self-Supervised Learning (HSSL), a new self-supervised framework that boosts medical image segmentation by making good ...
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We propose instead a framework for pixel-level (dense) representation learn- ing, dubbed Pix2Rep, which can be used to pretrain encoder-decoder architectures,.
Self-supervised learning (SSL) has shown great potentials in exploiting raw data information and representation learning. In this paper, we propose Hierarchical ...