<p>The architectures of the 3D single view CNN (SV-CNN) (top) and 3D MV-CNN (bottom).</p
<p>Three-dimensional reconstruction neuroimages of brain at different structures (vertical view).</p
The parameters within the parenthesis indicate the kernel dimension, stride and padding. By skipping...
The field of view (FOV), i.e. the input patch size, is 33 × 33 × 7 voxels and the output is the segm...
<p>Architecture of the fully connected CNN with a 3 layer “U-Net” architecture.</p
<p>CNN-1 is composed of three layers, two convolutional layers and an output layer.</p
CNN architectures. a) Stack, b) Concatenate, and c) our novel Integrated approach.</p
Descriptions of each layer type may be found in the S1 Supporting Information.</p
<p>Schematic overview of our CNN architecture: The number of output classes was set to 2 (melanoma a...
The architecture has three blocks: a convolutional block (CNN), a recursive block (LSTM), and a fina...
Computer vision is becoming an increasingly trendy word in the area of image processing. With the em...
(A) Surrounding environment extraction. The magenta color depicts the nucleotide under assessment. B...
Deep Convolutional Neural Network (CNN) architectures for the 3 different networks that we employed:...
This is the code of the framework for multimodal 3D registration of CT volumes and 3D point clouds w...
The architecture of proposed feature fusion LSTM-CNN model comprised of SC-CNN and ST-LSTM models.</...
<p>Since architectures of all the six sub-networks are the same, only one of them is shown here (lef...
<p>Three-dimensional reconstruction neuroimages of brain at different structures (vertical view).</p
The parameters within the parenthesis indicate the kernel dimension, stride and padding. By skipping...
The field of view (FOV), i.e. the input patch size, is 33 × 33 × 7 voxels and the output is the segm...
<p>Architecture of the fully connected CNN with a 3 layer “U-Net” architecture.</p
<p>CNN-1 is composed of three layers, two convolutional layers and an output layer.</p
CNN architectures. a) Stack, b) Concatenate, and c) our novel Integrated approach.</p
Descriptions of each layer type may be found in the S1 Supporting Information.</p
<p>Schematic overview of our CNN architecture: The number of output classes was set to 2 (melanoma a...
The architecture has three blocks: a convolutional block (CNN), a recursive block (LSTM), and a fina...
Computer vision is becoming an increasingly trendy word in the area of image processing. With the em...
(A) Surrounding environment extraction. The magenta color depicts the nucleotide under assessment. B...
Deep Convolutional Neural Network (CNN) architectures for the 3 different networks that we employed:...
This is the code of the framework for multimodal 3D registration of CT volumes and 3D point clouds w...
The architecture of proposed feature fusion LSTM-CNN model comprised of SC-CNN and ST-LSTM models.</...
<p>Since architectures of all the six sub-networks are the same, only one of them is shown here (lef...
<p>Three-dimensional reconstruction neuroimages of brain at different structures (vertical view).</p
The parameters within the parenthesis indicate the kernel dimension, stride and padding. By skipping...
The field of view (FOV), i.e. the input patch size, is 33 × 33 × 7 voxels and the output is the segm...
DOI