Workflow of DeephESC 2.0 is split into three modules namely: Detection of hESC from video, Generation of synthetic hESC images and hierarchical classification of the hESC images into six different classes.</p
Over the past few years deep learning has demonstrated impressive performance on many important prac...
We present recent work in supporting deep learning for particle physics and cosmology at NERSC, the ...
High-Efficiency Video Coding provides a better compression ratio compared to earlier standard, H.264...
Visualization of features extracted by the CNN in DeephESC 2.0 for (a) Apoptically Blebbing cell and...
Human embryonic stem cells (hESC), derived from the blastocysts, provide unique cellular models for ...
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 architecture of De...
Confusion matrix for the classification of the 724 real hESC images using the CNN-Triplet architectu...
High Efficiency Video Coding (HEVC) is also know as H.265 was first official introduced in 2013, it ...
Comparison of the average classification accuracy of the networks used in DeephESC and DeephESC 2.0....
Hi-C is commonly used to study three-dimensional genome organization. However, due to the high seque...
Initial studies have suggested generative adversarial networks (GANs) have promise as fast simulatio...
Tesis (Maestría en Ciencias en Ingeniería de Cómputo), Instituto Politécnico Nacional, SEPI, CIC, 20...
This paper proposes a fast algorithm to reduce the high computational complexity of depth map coding...
Automated understanding of human embryonic stem cell (hESC) videos is essential for the quantified a...
Over the past few years deep learning has demonstrated impressive performance on many important prac...
We present recent work in supporting deep learning for particle physics and cosmology at NERSC, the ...
High-Efficiency Video Coding provides a better compression ratio compared to earlier standard, H.264...
Visualization of features extracted by the CNN in DeephESC 2.0 for (a) Apoptically Blebbing cell and...
Human embryonic stem cells (hESC), derived from the blastocysts, provide unique cellular models for ...
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 architecture of De...
Confusion matrix for the classification of the 724 real hESC images using the CNN-Triplet architectu...
High Efficiency Video Coding (HEVC) is also know as H.265 was first official introduced in 2013, it ...
Comparison of the average classification accuracy of the networks used in DeephESC and DeephESC 2.0....
Hi-C is commonly used to study three-dimensional genome organization. However, due to the high seque...
Initial studies have suggested generative adversarial networks (GANs) have promise as fast simulatio...
Tesis (Maestría en Ciencias en Ingeniería de Cómputo), Instituto Politécnico Nacional, SEPI, CIC, 20...
This paper proposes a fast algorithm to reduce the high computational complexity of depth map coding...
Automated understanding of human embryonic stem cell (hESC) videos is essential for the quantified a...
Over the past few years deep learning has demonstrated impressive performance on many important prac...
We present recent work in supporting deep learning for particle physics and cosmology at NERSC, the ...
High-Efficiency Video Coding provides a better compression ratio compared to earlier standard, H.264...
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