mobilenet v2 Search Results


mobilenet-v2  (RenderX Inc)
90
RenderX Inc mobilenet-v2
Mobilenet V2, supplied by RenderX Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/mobilenet+v2/mobilenet+v2/pm36018623-90-17-13
Average 90 stars, based on 1 article reviews
mobilenet-v2 - by Bioz Stars, 2026-09
90/100 stars
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dcnn: mobilenet v2  (EyePACS LLC)
90
EyePACS LLC dcnn: mobilenet v2
Classification-based studies in DR detection using fundus imaging.
Dcnn: Mobilenet V2, supplied by EyePACS LLC, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/mobilenet+v2/dcnn++mobilenet+v2/pmc08468161-101-16-5
Average 90 stars, based on 1 article reviews
dcnn: mobilenet v2 - by Bioz Stars, 2026-09
90/100 stars
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pretrained mobilenet v2 models  (Altera Corp)
86
Altera Corp pretrained mobilenet v2 models
Confusion matrix for classification performance on the FER2013 dataset <t>by</t> <t>MobileNet‐v2</t> models with (A) floating‐point weights (FP32), MSD approximated weights with (B) p = 3, (C) p = 2 and (D) p = 1.
Pretrained Mobilenet V2 Models, supplied by Altera Corp, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/mobilenet+v2/mobilenet+models+pretrained+v2/pmc12807348-170-1-11
Average 86 stars, based on 1 article reviews
pretrained mobilenet v2 models - by Bioz Stars, 2026-09
86/100 stars
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Image Search Results


Classification-based studies in DR detection using fundus imaging.

Journal: Journal of Imaging

Article Title: Automated Detection and Diagnosis of Diabetic Retinopathy: A Comprehensive Survey

doi: 10.3390/jimaging7090165

Figure Lengend Snippet: Classification-based studies in DR detection using fundus imaging.

Article Snippet: Patel, 2020 [ ] , EyePACS , Grade DR based on ICDR scale , Yes , DCNN: MobileNet v2 , 91.29% , NA , NA , NA.

Techniques: Imaging, Modification, Extraction

Classification-based studies in DR detection using OCT and OCTA.

Journal: Journal of Imaging

Article Title: Automated Detection and Diagnosis of Diabetic Retinopathy: A Comprehensive Survey

doi: 10.3390/jimaging7090165

Figure Lengend Snippet: Classification-based studies in DR detection using OCT and OCTA.

Article Snippet: Patel, 2020 [ ] , EyePACS , Grade DR based on ICDR scale , Yes , DCNN: MobileNet v2 , 91.29% , NA , NA , NA.

Techniques: Extraction

Segmentation-based studies in DR detection using fundus images.

Journal: Journal of Imaging

Article Title: Automated Detection and Diagnosis of Diabetic Retinopathy: A Comprehensive Survey

doi: 10.3390/jimaging7090165

Figure Lengend Snippet: Segmentation-based studies in DR detection using fundus images.

Article Snippet: Patel, 2020 [ ] , EyePACS , Grade DR based on ICDR scale , Yes , DCNN: MobileNet v2 , 91.29% , NA , NA , NA.

Techniques: Extraction

Segmentation-based studies in DR detection using OCT, OCTA images.

Journal: Journal of Imaging

Article Title: Automated Detection and Diagnosis of Diabetic Retinopathy: A Comprehensive Survey

doi: 10.3390/jimaging7090165

Figure Lengend Snippet: Segmentation-based studies in DR detection using OCT, OCTA images.

Article Snippet: Patel, 2020 [ ] , EyePACS , Grade DR based on ICDR scale , Yes , DCNN: MobileNet v2 , 91.29% , NA , NA , NA.

Techniques: Control, Extraction

Confusion matrix for classification performance on the FER2013 dataset by MobileNet‐v2 models with (A) floating‐point weights (FP32), MSD approximated weights with (B) p = 3, (C) p = 2 and (D) p = 1.

Journal: Quantitative Biology

Article Title: Secure and efficient implementation of facial emotion detection for smart patient monitoring system

doi: 10.15302/J-QB-022-0312

Figure Lengend Snippet: Confusion matrix for classification performance on the FER2013 dataset by MobileNet‐v2 models with (A) floating‐point weights (FP32), MSD approximated weights with (B) p = 3, (C) p = 2 and (D) p = 1.

Article Snippet: The pretrained MobileNet‐v2 models with approximated weights were implemented on the Altera DE4 development board using the Quartus Prime Pro software package.

Techniques: