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Advanced Search Results For "SUPERVISED learning"

1 - 10 of 17,371 results for
 "SUPERVISED learning"
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Unsupervised and semi-supervised learning: the next frontier in machine learning for plant systems biology.

Publication Type:Academic Journal

Source(s):The Plant journal : for cell and molecular biology [Plant J] 2022 Sep; Vol. 111 (6), pp. 1527-1538. Date of Electronic Publication: 2022 Jul 27.

Abstract:Advances in high-throughput omics technologies are leading plant biology research into the era of big data. Machine learning (ML) performs an important role in plant systems biology because of its excellent performance and wide application in the analy...

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What Actually Works for Activity Recognition in Scenarios with Significant Domain Shift: Lessons Learned from the 2019 and 2020 Sussex-Huawei Challenges.

Publication Type:Academic Journal

Source(s):Sensors (Basel, Switzerland) [Sensors (Basel)] 2022 May 10; Vol. 22 (10). Date of Electronic Publication: 2022 May 10.

Abstract:From 2018 to 2021, the Sussex-Huawei Locomotion-Transportation Recognition Challenge presented different scenarios in which participants were tasked with recognizing eight different modes of locomotion and transportation using sensor data from smartpho...

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Segmentation only uses sparse annotations: Unified weakly and semi-supervised learning in medical images.

Publication Type:Academic Journal

Source(s):Medical image analysis [Med Image Anal] 2022 Aug; Vol. 80, pp. 102515. Date of Electronic Publication: 2022 Jun 17.

Abstract:Since segmentation labeling is usually time-consuming and annotating medical images requires professional expertise, it is laborious to obtain a large-scale, high-quality annotated segmentation dataset. We propose a novel weakly- and semi-supervised fr...

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Recent advances and clinical applications of deep learning in medical image analysis.

Publication Type:Academic Journal

Source(s):Medical image analysis [Med Image Anal] 2022 Jul; Vol. 79, pp. 102444. Date of Electronic Publication: 2022 Apr 04.

Abstract:Deep learning has received extensive research interest in developing new medical image processing algorithms, and deep learning based models have been remarkably successful in a variety of medical imaging tasks to support disease detection and diagnosi...

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MultiHeadGAN: A deep learning method for low contrast retinal pigment epithelium cell segmentation with fluorescent flatmount microscopy images.

Publication Type:Academic Journal

Source(s):Computers in biology and medicine [Comput Biol Med] 2022 Jul; Vol. 146, pp. 105596. Date of Electronic Publication: 2022 May 10.

Abstract:Background: Retinal pigment epithelium (RPE) aging is an important cause of vision loss. As RPE aging is accompanied by changes in cell morphological features, an accurate segmentation of RPE cells is a prerequisite to such morphology analyses. Due the...

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TSRNet: Diagnosis of COVID-19 based on self-supervised learning and hybrid ensemble model.

Publication Type:Academic Journal

Source(s):Computers in biology and medicine [Comput Biol Med] 2022 Jul; Vol. 146, pp. 105531. Date of Electronic Publication: 2022 Apr 16.

Abstract:Background: As of Feb 27, 2022, coronavirus (COVID-19) has caused 434,888,591 infections and 5,958,849 deaths worldwide, dealing a severe blow to the economies and cultures of most countries around the world. As the virus has mutated, its infectious ca...

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An Efficient Semi-Supervised Framework with Multi-Task and Curriculum Learning for Medical Image Segmentation.

Publication Type:Academic Journal

Source(s):International journal of neural systems [Int J Neural Syst] 2022 Sep; Vol. 32 (9), pp. 2250043. Date of Electronic Publication: 2022 Jul 30.

Abstract:A practical problem in supervised deep learning for medical image segmentation is the lack of labeled data which is expensive and time-consuming to acquire. In contrast, there is a considerable amount of unlabeled data available in the clinic. To make ...

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Using Sparse Patch Annotation for Tumor Segmentation in Histopathological Images.

Publication Type:Academic Journal

Source(s):Sensors (Basel, Switzerland) [Sensors (Basel)] 2022 Aug 13; Vol. 22 (16). Date of Electronic Publication: 2022 Aug 13.

Abstract:Tumor segmentation is a fundamental task in histopathological image analysis. Creating accurate pixel-wise annotations for such segmentation tasks in a fully-supervised training framework requires significant effort. To reduce the burden of manual anno...

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MB-SupCon: Microbiome-based Predictive Models via Supervised Contrastive Learning.

Publication Type:Academic Journal

Source(s):Journal of molecular biology [J Mol Biol] 2022 Aug 15; Vol. 434 (15), pp. 167693. Date of Electronic Publication: 2022 Jun 28.

Abstract:Human microbiome consists of trillions of microorganisms. Microbiota can modulate the host physiology through molecule and metabolite interactions. Integrating microbiome and metabolomics data have the potential to predict different diseases more accur...

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Weakly supervised segmentation on neural compressed histopathology with self-equivariant regularization.

Publication Type:Academic Journal

Source(s):Medical image analysis [Med Image Anal] 2022 Aug; Vol. 80, pp. 102482. Date of Electronic Publication: 2022 May 25.

Abstract:In digital pathology, segmentation is a fundamental task for the diagnosis and treatment of diseases. Existing fully supervised methods often require accurate pixel-level annotations that are both time-consuming and laborious to generate. Typical appro...

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