Aug 9, 2022 · We compared the efficacy of recent self-supervised and transfer learning approaches to provide a base encoder to a high throughput artefact image detector.
Feb 14, 2023 · We compared the efficacy of recent self-supervised and transfer learning approaches to provide a base encoder to a high throughput artefact image detector.
Aug 9, 2022 · The results of this study suggest that transfer learning methods should be preferred for this task as they not only performed best here but ...
Progress in automated microscopy and quantitative image analysis has promoted high-content screening (HCS) as an efficient drug discovery and research tool.
Comparison of Semi-supervised Learning Methods for High Content Screening Quality Control · List of references · Publications that cite this publication.
People also ask
What are the benefits of semi-supervised learning?
What is the difference between semi-supervised learning?
What is the difference between transductive learning and semi-supervised learning?
What is the difference between semi-supervised learning and active learning?
In this paper, we propose a novel scheme that uses QC of the downstream task to identify high quality outputs of CMR segmentation networks.
Missing: Screening | Show results with:Screening
Overall, review aims to provide an extensive comparative analysis of semi-supervised methods for medical image classification task based on loss function ...
Apr 15, 2024 · This article introduces the SSL-WSC algorithm, which classifies unlabeled data through semi-supervised self-training learning using a small ...
This study aims to analyze the effectiveness of several semi-supervised learning approaches for opinion spam classification.
Missing: Comparison Screening Control.
Sep 19, 2024 · Experimental results demonstrate that the proposed method outperforms the current state-of-the-art (SOTA) semi-supervised semantic segmentation ...