AIMC Topic: Neural Networks, Computer

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A Deep Learning and Clustering Extraction Mechanism for Recognizing the Actions of Athletes in Sports.

Computational intelligence and neuroscience
In sports, the essence of a complete technical action is a complete information structure pattern and the athlete's judgment of the action is actually the identification of the movement information structure pattern. Action recognition refers to the ...

Nonlinear Network Speech Recognition Structure in a Deep Learning Algorithm.

Computational intelligence and neuroscience
As a result of the fast rise of globalization, people in China are learning English at a rapid pace. However, there is a severe shortage of English teachers in the region, which is a major hindrance. To address these concerns, a deep learning-based a...

A fully automated sex estimation for proximal femur X-ray images through deep learning detection and classification.

Legal medicine (Tokyo, Japan)
PURPOSE: To develop a fully automated deep learning pipeline using digital radiographs to detect the proximal femur region for accurate automated sex estimation.

Guaranteed approximation error estimation of neural networks and model modification.

Neural networks : the official journal of the International Neural Network Society
Approximation error is a key measure in the process of model validation and verification for neural networks. In this paper, the problems of guaranteed error estimation of neural networks and applications to assured system modeling and assured neural...

Exploration in neo-Hebbian reinforcement learning: Computational approaches to the exploration-exploitation balance with bio-inspired neural networks.

Neural networks : the official journal of the International Neural Network Society
Recent theoretical and experimental works have connected Hebbian plasticity with the reinforcement learning (RL) paradigm, producing a class of trial-and-error learning in artificial neural networks known as neo-Hebbian plasticity. Inspired by the ro...

Medical image diagnosis of prostate tumor based on PSP-Net+VGG16 deep learning network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Prostate cancer is the most common cancer of the male reproductive system. With the development of medical imaging technology, magnetic resonance images (MRI) have been used in the diagnosis and treatment of prostate cancer ...

A visually interpretable detection method combines 3-D ECG with a multi-VGG neural network for myocardial infarction identification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The automatic recognition of myocardial infarction (MI) by artificial intelligence (AI) has been an emerging topic of academic research and an existing classification method that can recognize conventional electrocardiogram ...

Improving convolutional neural network learning based on a hierarchical bezier generative model for stenosis detection in X-ray images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Automatic detection of stenosis on X-ray Coronary Angiography (XCA) images may help diagnose early coronary artery disease. Stenosis is manifested by a buildup of plaque in the arteries, decreasing the blood flow to the hear...

A ensemble methodology for automatic classification of chest X-rays using deep learning.

Computers in biology and medicine
Chest radiographies, or chest X-rays, are the most standard imaging exams used in daily hospitals. Responsible for assisting in detecting numerous pathologies and findings that directly interfere in the patient's life, this exam is therefore crucial ...

Word-level text highlighting of medical texts for telehealth services.

Artificial intelligence in medicine
The medical domain is often subject to information overload. The digitization of healthcare, constant updates to online medical repositories, and increasing availability of biomedical datasets make it challenging to effectively analyze the data. This...