AIMC Topic: Neural Networks, Computer

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An Improved COVID-19 Detection using GAN-Based Data Augmentation and Novel QuNet-Based Classification.

BioMed research international
COVID-19 is a fatal disease caused by the SARS-CoV-2 virus that has caused around 5.3 Million deaths globally as of December 2021. The detection of this disease is a time taking process that have worsen the situation around the globe, and the disease...

Performance Degradation Estimation of High-Speed Train Bogie Based on 1D-ConvLSTM Time-Distributed Convolutional Neural Network.

Computational intelligence and neuroscience
High-speed train bogies are essential for the safety and comfort of train operation. The performance of the bogie usually degrades before it fails, so it is necessary to detect the performance degradation of a high-speed train bogie in advance. In th...

A deep reinforcement transfer convolutional neural network for rolling bearing fault diagnosis.

ISA transactions
Deep neural networks highly depend on substantial labeled samples when identifying bearing fault. However, in some practical situations, it is very difficult to collect sufficient labeled samples, which limits the application of deep neural networks ...

Secure predictor-based neural dynamic surface control of nonlinear cyber-physical systems against sensor and actuator attacks.

ISA transactions
This paper addresses a secure predictor-based neural dynamic surface control (SPNDSC) issue for a cyber-physical system in a nontriangular form suffering from both sensor and actuator deception attacks. To avoid the algebraic loop problem, only parti...

Efficient learning rate adaptation based on hierarchical optimization approach.

Neural networks : the official journal of the International Neural Network Society
This paper proposes a new hierarchical approach to learning rate adaptation in gradient methods, called learning rate optimization (LRO). LRO formulates the learning rate adaption problem as a hierarchical optimization problem that minimizes the loss...

Towards improving fast adversarial training in multi-exit network.

Neural networks : the official journal of the International Neural Network Society
Adversarial examples are usually generated by adding adversarial perturbations on clean samples, designed to deceive the model to make wrong classifications. Adversarial robustness refers to the ability of a model to resist adversarial attacks. And c...

A Multilevel Transfer Learning Technique and LSTM Framework for Generating Medical Captions for Limited CT and DBT Images.

Journal of digital imaging
Medical image captioning has been recently attracting the attention of the medical community. Also, generating captions for images involving multiple organs is an even more challenging task. Therefore, any attempt toward such medical image captioning...

Convolutional neural network is a good technique for sleep staging based on HRV: A comparative analysis.

Neuroscience letters
The fluctuation of heart rate is regulated by autonomic nervous system. In human sleep, the autonomic nervous system plays a leading role. Therefore, we can use heart-rate variability (HRV) to stage the sleep process. Based on two independent public ...

Curv-Net: Curvilinear structure segmentation network based on selective kernel and multi-Bi-ConvLSTM.

Medical physics
PURPOSE: Accurately segmenting curvilinear structures, for example, retinal blood vessels or nerve fibers, in the medical image is essential to the clinical diagnosis of many diseases. Recently, deep learning has become a popular technology to deal w...

PathDetect-SOM: A Neural Network Approach for the Identification of Pathways in Ligand Binding Simulations.

Journal of chemical theory and computation
Understanding the process of ligand-protein recognition is important to unveil biological mechanisms and to guide drug discovery and design. Enhanced-sampling molecular dynamics is now routinely used to simulate the ligand binding process, resulting ...