Quantitative assessment of the effects of compression on deep learning in digital pathology image analysis
PURPOSE Deep learning (DL), a class of approaches involving self-learned discriminative
features, is increasingly being applied to digital pathology (DP) images for tasks such as …
features, is increasingly being applied to digital pathology (DP) images for tasks such as …
Quantitative Assessment of the Effects of Compression on Deep Learning in Digital Pathology Image Analysis.
Y Chen, A Janowczyk, A Madabhushi - JCO Clinical Cancer …, 2020 - europepmc.org
Purpose Deep learning (DL), a class of approaches involving self-learned discriminative
features, is increasingly being applied to digital pathology (DP) images for tasks such as …
features, is increasingly being applied to digital pathology (DP) images for tasks such as …
Quantitative Assessment of the Effects of Compression on Deep Learning in Digital Pathology Image Analysis
Y Chen, A Janowczyk… - JCO clinical cancer …, 2020 - pubmed.ncbi.nlm.nih.gov
Purpose Deep learning (DL), a class of approaches involving self-learned discriminative
features, is increasingly being applied to digital pathology (DP) images for tasks such as …
features, is increasingly being applied to digital pathology (DP) images for tasks such as …
[PDF][PDF] Quantitative Assessment of the Effects of Compression on Deep Learning in Digital Pathology Image Analysis
BS Yijiang Chen - 2020 - researchgate.net
METHODS We investigated the effects of image compression on the performance of DL
strategies in the context of 3 representative use cases involving segmentation of nuclei (n …
strategies in the context of 3 representative use cases involving segmentation of nuclei (n …
[PDF][PDF] Quantitative Assessment of the Effects of Compression on Deep Learning in Digital Pathology Image Analysis
BS Yijiang Chen - pdfs.semanticscholar.org
METHODS We investigated the effects of image compression on the performance of DL
strategies in the context of 3 representative use cases involving segmentation of nuclei (n …
strategies in the context of 3 representative use cases involving segmentation of nuclei (n …
[HTML][HTML] Quantitative Assessment of the Effects of Compression on Deep Learning in Digital Pathology Image Analysis
Y Chen, A Janowczyk… - JCO Clinical Cancer …, 2020 - ncbi.nlm.nih.gov
PURPOSE Deep learning (DL), a class of approaches involving self-learned discriminative
features, is increasingly being applied to digital pathology (DP) images for tasks such as …
features, is increasingly being applied to digital pathology (DP) images for tasks such as …
Quantitative Assessment of the Effects of Compression on Deep Learning in Digital Pathology Image Analysis
Y Chen, A Janowczyk, A Madabhushi - JCO Clinical Cancer Informatics - sonar.ch
English PURPOSE Deep learning (DL), a class of approaches involving self-learned
discriminative features, is increasingly being applied to digital pathology (DP) images for …
discriminative features, is increasingly being applied to digital pathology (DP) images for …
[PDF][PDF] Quantitative Assessment of the Effects of Compression on Deep Learning in Digital Pathology Image Analysis
BS Yijiang Chen - serval.unil.ch
METHODS We investigated the effects of image compression on the performance of DL
strategies in the context of 3 representative use cases involving segmentation of nuclei (n …
strategies in the context of 3 representative use cases involving segmentation of nuclei (n …
Quantitative Assessment of the Effects of Compression on Deep Learning in Digital Pathology Image Analysis
Y Chen, A Janowczyk, A Madabhushi - JCO Clinical Cancer Informatics - folia.unifr.ch
English PURPOSE Deep learning (DL), a class of approaches involving self-learned
discriminative features, is increasingly being applied to digital pathology (DP) images for …
discriminative features, is increasingly being applied to digital pathology (DP) images for …
[PDF][PDF] Quantitative Assessment of the Effects of Compression on Deep Learning in Digital Pathology Image Analysis
BS Yijiang Chen - serval.unil.ch
METHODS We investigated the effects of image compression on the performance of DL
strategies in the context of 3 representative use cases involving segmentation of nuclei (n …
strategies in the context of 3 representative use cases involving segmentation of nuclei (n …