DeephESC 2.0: Deep Generative Multi Adversarial Networks for improving the classification of hESC - Fig 11

Studying the Applicability of Generative Adversarial Networks on HEp-2 Cell Image Augmentation

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Hani M. Bu-Omer
Akio Gofuku

January 2021

The Anti-Nuclear Antibodies (ANAs) testing is the primary serological diagnosis screening test for a...

Deep Learning Applied for Histological Diagnosis of Beat Cancer

Nguyen, Hieu

January 2020

Deep learning, as one of the currently most popular computer science research trends, improves neura...

Deep CNN and Deep GAN in Computational Visual Perception-Driven Image Analysis

R. Nandhini Abirami
P. M. Durai Raj Vincent
Kathiravan Srinivasan
Usman Tariq
Chuan-Yu Chang

January 2021

Computational visual perception, also known as computer vision, is a field of artificial intelligenc...

DeephESC 2.0: Deep Generative Multi Adversarial Networks for improving the classification of hESC - Fig 5

Rajkumar Theagarajan (6429590)
Bir Bhanu (2154277)

March 2019

Workflow of DeephESC 2.0 is split into three modules namely: Detection of hESC from video, Generatio...

DeephESC 2.0: Deep Generative Multi Adversarial Networks for improving the classification of hESC.

Theagarajan, Rajkumar
Bhanu, Bir

January 2019

Human embryonic stem cells (hESC), derived from the blastocysts, provide unique cellular models for ...

Visualization of features learned by DeephESC 2.0.

Rajkumar Theagarajan (6429590)
Bir Bhanu (2154277)

March 2019

(a) Image of a Cell cluster. (b) Image after masking the surrounding small cells using a window. Red...

Confusion matrix for the classification of the 724 real hESC images using the CNN architecture of DeephESC 2.0.

Rajkumar Theagarajan (6429590)
Bir Bhanu (2154277)

March 2019

Confusion matrix for the classification of the 724 real hESC images using the CNN architecture of De...

Confusion matrix for the classification of the 724 real hESC images using the Fused CNN-Triplet architecture of DeephESC 2.0.

Rajkumar Theagarajan (6429590)
Bir Bhanu (2154277)

March 2019

Confusion matrix for the classification of the 724 real hESC images using the Fused CNN-Triplet arch...

Confusion matrix for the classification of the 724 real hESC images using the CNN-Triplet architecture of DeephESC 2.0.

Rajkumar Theagarajan (6429590)
Bir Bhanu (2154277)

March 2019

Confusion matrix for the classification of the 724 real hESC images using the CNN-Triplet architectu...

HEp-2 Cell Image Classification with Deep Convolutional Neural Networks

Gao, Zhimin
Wang, Lei
Zhou, Luping
Zhang, Jianjia

January 2017

2017 IEEE.Efficient Human Epithelial-2 cell image classification can facilitate the diagnosis of man...

HEp-2 Cell Image Classification With Deep Convolutional Neural Networks.

Gao, Z
Wang, L
Zhou, L
Zhang, J

July 2022

Efficient Human Epithelial-2 cell image classification can facilitate the diagnosis of many autoimmu...

Architecture of Triplet CNN A and Triplet CNN B in Fig 8.

Rajkumar Theagarajan (6429590)
Bir Bhanu (2154277)

March 2019

The parameters within the parenthesis indicate the kernel dimension, stride and padding. By skipping...

Automated Stain‐Free Holographic Image‐Based Phenotypic Classification of Elliptical Cancer Cells

Kevyan Jaferzadeh
Seungwoo Son
Abdur Rehman
Seonghwan Park
Inkyu Moon

January 2023

Image‐based stain‐free elliptical cancer cell classification is very challenging due to interclass m...

Human embryonic stem cell classification: random network with autoencoded feature extractor.

Guan, Benjamin X
Bhanu, Bir
Theagarajan, Rajkumar
Liu, Hengyue
Talbot, Prue
Weng, Nikki

April 2021

Automated understanding of human embryonic stem cell (hESC) videos is essential for the quantified a...

Classification of Breast Cancer Histopathological Images Using Semi-Supervised GANs

Avvaru, Balaji
Lohia, Nibhrat
Mani, Sowmya
kaniti, Vijayasrikanth

September 2022

Breast cancer is diagnosed more frequently than skin cancer in women in the United States. Most brea...

Studying the Applicability of Generative Adversarial Networks on HEp-2 Cell Image Augmentation

Asaad Anaam
Hani M. Bu-Omer
Akio Gofuku

January 2021

The Anti-Nuclear Antibodies (ANAs) testing is the primary serological diagnosis screening test for a...

Deep Learning Applied for Histological Diagnosis of Beat Cancer

Nguyen, Hieu

January 2020

Deep learning, as one of the currently most popular computer science research trends, improves neura...

Deep CNN and Deep GAN in Computational Visual Perception-Driven Image Analysis

R. Nandhini Abirami
P. M. Durai Raj Vincent
Kathiravan Srinivasan
Usman Tariq
Chuan-Yu Chang

January 2021

Computational visual perception, also known as computer vision, is a field of artificial intelligenc...

DeephESC 2.0: Deep Generative Multi Adversarial Networks for improving the classification of hESC - Fig 5

Rajkumar Theagarajan (6429590)
Bir Bhanu (2154277)

March 2019

Workflow of DeephESC 2.0 is split into three modules namely: Detection of hESC from video, Generatio...

DeephESC 2.0: Deep Generative Multi Adversarial Networks for improving the classification of hESC.

Theagarajan, Rajkumar
Bhanu, Bir

January 2019

Human embryonic stem cells (hESC), derived from the blastocysts, provide unique cellular models for ...

Visualization of features learned by DeephESC 2.0.

Rajkumar Theagarajan (6429590)
Bir Bhanu (2154277)

March 2019

(a) Image of a Cell cluster. (b) Image after masking the surrounding small cells using a window. Red...

Confusion matrix for the classification of the 724 real hESC images using the CNN architecture of DeephESC 2.0.

Rajkumar Theagarajan (6429590)
Bir Bhanu (2154277)

March 2019

Confusion matrix for the classification of the 724 real hESC images using the CNN architecture of De...

Confusion matrix for the classification of the 724 real hESC images using the Fused CNN-Triplet architecture of DeephESC 2.0.

Rajkumar Theagarajan (6429590)
Bir Bhanu (2154277)

March 2019

Confusion matrix for the classification of the 724 real hESC images using the Fused CNN-Triplet arch...

Confusion matrix for the classification of the 724 real hESC images using the CNN-Triplet architecture of DeephESC 2.0.

Rajkumar Theagarajan (6429590)
Bir Bhanu (2154277)

March 2019

Confusion matrix for the classification of the 724 real hESC images using the CNN-Triplet architectu...

HEp-2 Cell Image Classification with Deep Convolutional Neural Networks

Gao, Zhimin
Wang, Lei
Zhou, Luping
Zhang, Jianjia

January 2017

2017 IEEE.Efficient Human Epithelial-2 cell image classification can facilitate the diagnosis of man...

HEp-2 Cell Image Classification With Deep Convolutional Neural Networks.

Gao, Z
Wang, L
Zhou, L
Zhang, J

July 2022

Efficient Human Epithelial-2 cell image classification can facilitate the diagnosis of many autoimmu...

Architecture of Triplet CNN A and Triplet CNN B in Fig 8.

Rajkumar Theagarajan (6429590)
Bir Bhanu (2154277)

March 2019

The parameters within the parenthesis indicate the kernel dimension, stride and padding. By skipping...

Automated Stain‐Free Holographic Image‐Based Phenotypic Classification of Elliptical Cancer Cells

Kevyan Jaferzadeh
Seungwoo Son
Abdur Rehman
Seonghwan Park
Inkyu Moon

January 2023

Image‐based stain‐free elliptical cancer cell classification is very challenging due to interclass m...

Human embryonic stem cell classification: random network with autoencoded feature extractor.

Guan, Benjamin X
Bhanu, Bir
Theagarajan, Rajkumar
Liu, Hengyue
Talbot, Prue
Weng, Nikki

April 2021

Automated understanding of human embryonic stem cell (hESC) videos is essential for the quantified a...

Classification of Breast Cancer Histopathological Images Using Semi-Supervised GANs

Avvaru, Balaji
Lohia, Nibhrat
Mani, Sowmya
kaniti, Vijayasrikanth

September 2022

Breast cancer is diagnosed more frequently than skin cancer in women in the United States. Most brea...

Studying the Applicability of Generative Adversarial Networks on HEp-2 Cell Image Augmentation

Asaad Anaam
Hani M. Bu-Omer
Akio Gofuku

January 2021

The Anti-Nuclear Antibodies (ANAs) testing is the primary serological diagnosis screening test for a...

Deep Learning Applied for Histological Diagnosis of Beat Cancer

Nguyen, Hieu

January 2020

Deep learning, as one of the currently most popular computer science research trends, improves neura...

Deep CNN and Deep GAN in Computational Visual Perception-Driven Image Analysis

R. Nandhini Abirami
P. M. Durai Raj Vincent
Kathiravan Srinivasan
Usman Tariq
Chuan-Yu Chang

January 2021

Computational visual perception, also known as computer vision, is a field of artificial intelligenc...

DeephESC 2.0: Deep Generative Multi Adversarial Networks for improving the classification of hESC - Fig 11

Abstract

Extracted data

DeephESC 2.0: Deep Generative Multi Adversarial Networks for improving the classification of hESC - Fig 11

Abstract

Extracted data

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