inception-v3 architecture Search Results


90
EyePACS LLC inception-v3 architecture
Studies that implement deep learning techniques for the detection of DR.
Inception V3 Architecture, 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
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86
Kaggle Inc inceptionv3 architecture
Studies that implement deep learning techniques for the detection of DR.
Inceptionv3 Architecture, supplied by Kaggle Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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90
EyePACS LLC resnet-50
Studies that implement deep learning techniques for the detection of DR.
Resnet 50, 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
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SoftMax Inc inception v3 architecture
The input size for each DL architecture [ <xref ref-type= 29 ]." width="250" height="auto" />
Inception V3 Architecture, supplied by SoftMax 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/inception-v3+architecture/inceptionv3+++softmax/pmc09546660-115-11-1
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Image Search Results


Studies that implement deep learning techniques for the detection of DR.

Journal: Sensors (Basel, Switzerland)

Article Title: Severity Grading and Early Retinopathy Lesion Detection through Hybrid Inception-ResNet Architecture

doi: 10.3390/s21206933

Figure Lengend Snippet: Studies that implement deep learning techniques for the detection of DR.

Article Snippet: Gulshan et al., 2016 [ ] , A collection of Inception-V3 architecture that is trained on more than 100,000 images, including many grades for each image and two images for each subject , Messidor-2, Private and (EyePACS)-1 , Required for a recommendation of diabetic retinopathy on Messidor-2.

Techniques: Selection

The input size for each DL architecture [ <xref ref-type= 29 ]." width="100%" height="100%">

Journal: Computational Intelligence and Neuroscience

Article Title: Diagnosis of Oral Squamous Cell Carcinoma Using Deep Neural Networks and Binary Particle Swarm Optimization on Histopathological Images: An AIoMT Approach

doi: 10.1155/2022/6364102

Figure Lengend Snippet: The input size for each DL architecture [ 29 ].

Article Snippet: The Softmax function is found in the last layer of the Inception V3 architecture [ ], which comprises 42 levels, where the resolution of the received information by the input layer in pixels is 299 × 299.

Techniques:

Inception V3 architecture schematic.

Journal: Computational Intelligence and Neuroscience

Article Title: Diagnosis of Oral Squamous Cell Carcinoma Using Deep Neural Networks and Binary Particle Swarm Optimization on Histopathological Images: An AIoMT Approach

doi: 10.1155/2022/6364102

Figure Lengend Snippet: Inception V3 architecture schematic.

Article Snippet: The Softmax function is found in the last layer of the Inception V3 architecture [ ], which comprises 42 levels, where the resolution of the received information by the input layer in pixels is 299 × 299.

Techniques:

Comparison of previous research works with the proposed method.

Journal: Computational Intelligence and Neuroscience

Article Title: Diagnosis of Oral Squamous Cell Carcinoma Using Deep Neural Networks and Binary Particle Swarm Optimization on Histopathological Images: An AIoMT Approach

doi: 10.1155/2022/6364102

Figure Lengend Snippet: Comparison of previous research works with the proposed method.

Article Snippet: The Softmax function is found in the last layer of the Inception V3 architecture [ ], which comprises 42 levels, where the resolution of the received information by the input layer in pixels is 299 × 299.

Techniques: Comparison, Biomarker Discovery