Deep convolutional neural network (DCNN) models have been widely explored for skin disease diagnosis and some of them have achieved the diagnostic outcomes comparable or even superior to those of dermatologists. However, broad implementation of DCNN ...
Respiratory motion is one of the main sources of motion artifacts in positron emission tomography (PET) imaging. The emission image and patient motion can be estimated simultaneously from respiratory gated data through a joint estimation framework. H...
IEEE transactions on neural networks and learning systems
May 2, 2022
Sensing and perception is generally a challenging aspect of decision-making. In the nanoscale, however, these processes face further complications due to the physical limitations of devising the nanomachines with more limited perception, more noise, ...
To address the problem of automatic identification of fine-grained fracture types, in this paper, we propose a novel framework using 3D convolutional neural network (CNN) to learn fracture features from voxelized bone models which are obtained by est...
Susceptibility induced distortion is a major artifact that affects the diffusion MRI (dMRI) data analysis. In the Human Connectome Project (HCP), the state-of-the-art method adopted to correct this kind of distortion is to exploit the displacement fi...
The outbreak of COVID-19 threatens the lives and property safety of countless people and brings a tremendous pressure to health care systems worldwide. The principal challenge in the fight against this disease is the lack of efficient detection metho...
IEEE transactions on neural networks and learning systems
May 2, 2022
Brain-inspired computing employs devices and architectures that emulate biological functions for more adaptive and energy-efficient systems. Oscillatory neural networks (ONNs) are an alternative approach in emulating biological functions of the human...
IEEE transactions on neural networks and learning systems
May 2, 2022
Surface electromyography (sEMG) signals have been applied widely in prosthetic hand controlling. In the sEMG signal acquisition, wireless devices bring convenience, but also introduce signal missing due to interference or failure during data transmis...
IEEE transactions on neural networks and learning systems
May 2, 2022
In the blast furnace ironmaking process, accurate prediction of silicon content in molten iron is of great significance for maintaining stable furnace conditions, improving hot metal quality, and reducing energy consumption. However, most of the curr...
IEEE transactions on neural networks and learning systems
May 2, 2022
A large number of studies have shown that astrocytes can be combined with the presynaptic terminals and postsynaptic spines of neurons to constitute a triple synapse via an endocannabinoid retrograde messenger to achieve a self-repair ability in the ...
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