As a rapid and automatic method, multiple radionuclide identification using deep learning has drawn wide interest ... In this study, we propose a CNN model with a channel attention module [20]. A ...

We consider a deep reinforcement learning (DRL) model representing a highway path planning policy for autonomous highway driving [1]. The model constitutes a mapping from the continuous ...

Abstract: The use of deep learning ... several modules at the transceivers would provide more significant gains. This article presents DL-based CSI feedback from the perspectives of a one-sided model ...

files ├── example_model/ : examples of model files ├── example_param/ : examples of parameter domain files ├── example_script/ : scripts for the examples ├── gcn_modules/ : ├── gcnvisualizer/ : kgcn ...

Researchers from Peking University have developed a novel noninvasive choroidal angiography method that enables layer-wise visualization and evaluation of choroidal vessels using deep learning.

There was an error while loading. Please reload this page. Note: This is not one convertor for all frameworks, but a collection of different converters. Because ...

Objective: To develop a deep learning (DL ... with ResUNet and PSPNet architectures. The model was trained on the PyTorch framework, thereby employing a combination of ResUNet and PSP modules. The ...