A novel semi-supervised learning framework with two branches, each consisting of an encoder and two decoders for geometry-aware constraints and pixel-level ...
Connected Papers is a visual tool to help researchers and applied scientists find academic papers relevant to their field of work.
Min-Max Similarity: A Contrastive Semi-Supervised Deep Learning Network for Surgical Tools Segmentation ... Segmentation via Geometry-aware Consistency Training ...
In this paper, we propose a novel contrastive learning-based semi-supervised technique – Min-Max Similarity (MMS) – to segment the surgical tools. Unlike the ...
We propose a semi-supervised medical image segmentation algorithm to reduce the dependence on labeled data.
Missing: Instrument | Show results with:Instrument
People also ask
Which segmentation technique is supervised or semi supervised?
In this paper, we propose a novel contrastive learning-based semi-supervised technique – Min-Max Similarity (MMS) – to segment the surgical tools. Unlike the ...
People also search for
Oct 22, 2024 · To address this issue, we proposed a semi-supervised segmentation network based on contrastive learning. In contrast to the previous state-of- ...
This paper introduces a novel semi-supervised learning strat- egy, amalgamating pseudo-labelling and contrastive learn- ing with a consistency regularization ...
Nov 6, 2024 · Compared to semi-supervised learning, unsupervised learning is fully annotation-free and is capable of prospecting more general and high-level ...
May 15, 2024 · In this work, we propose a framework for multi-task pixel-level representation learning that is led by certainty pixels.
Missing: Instrument | Show results with:Instrument