(a) Single Scale Regular Convolution (b), Multi-Scale Regular Convolution, and (c) Multi-Scale Depthwise Separable Convolution (Our proposed).</p
One of the most promising techniques used in various sciences is deep neural networks (DNNs). A spec...
Comparison between the number of voxels/octants used to achieve a resolution with a homogenous voxel...
We propose a block convolution algorithm that requires shorter length FFT than the conventional over...
Complexity comparison between the regular convolution kernel versus the depthwise separable convolut...
Comparison between the general convolutional neural network and the proposed model.</p
Comprehensive comparison between the algorithm proposed in this paper and other deep learning algori...
Convolution is the main building block of a convolutional neural network (CNN). We observe that an ...
In image classification, multi-scale information is usually combined by concatenating features or se...
The comparison of the proposed approach (DeepFocus) and Lopez's approach [3] for each slide on the t...
Research questions in several research domains imply the simultaneous analysis of different blocks o...
<p>The selected time-stamp is . (A) Original depth map. (B) Decoded depth map (QP = 48). (C) Reconst...
International audienceThis paper aims at understanding the role of multi-scale information in the es...
The object recognition concept is being widely used a result of increasing CCTV surveillance and the...
There is a growing interest in designing models that can deal with images from different visual doma...
The left, middle, and right sides represent standard convolution, deformable convolution, and T-defo...
One of the most promising techniques used in various sciences is deep neural networks (DNNs). A spec...
Comparison between the number of voxels/octants used to achieve a resolution with a homogenous voxel...
We propose a block convolution algorithm that requires shorter length FFT than the conventional over...
Complexity comparison between the regular convolution kernel versus the depthwise separable convolut...
Comparison between the general convolutional neural network and the proposed model.</p
Comprehensive comparison between the algorithm proposed in this paper and other deep learning algori...
Convolution is the main building block of a convolutional neural network (CNN). We observe that an ...
In image classification, multi-scale information is usually combined by concatenating features or se...
The comparison of the proposed approach (DeepFocus) and Lopez's approach [3] for each slide on the t...
Research questions in several research domains imply the simultaneous analysis of different blocks o...
<p>The selected time-stamp is . (A) Original depth map. (B) Decoded depth map (QP = 48). (C) Reconst...
International audienceThis paper aims at understanding the role of multi-scale information in the es...
The object recognition concept is being widely used a result of increasing CCTV surveillance and the...
There is a growing interest in designing models that can deal with images from different visual doma...
The left, middle, and right sides represent standard convolution, deformable convolution, and T-defo...
One of the most promising techniques used in various sciences is deep neural networks (DNNs). A spec...
Comparison between the number of voxels/octants used to achieve a resolution with a homogenous voxel...
We propose a block convolution algorithm that requires shorter length FFT than the conventional over...
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