AIMC Topic: Humans

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Comparison of neural basis expansion analysis for interpretable time series (N-BEATS) and recurrent neural networks for heart dysfunction classification.

Physiological measurement
The primary purpose of this work is to analyze the ability of N-BEATS architecture for the problem of prediction and classification of electrocardiogram (ECG) signals. To achieve this, performance comparison with various types of other SotA (state-of...

Logistic Regression-Based Model Is More Efficient Than U-Net Model for Reliable Whole Brain Magnetic Resonance Imaging Segmentation.

Topics in magnetic resonance imaging : TMRI
OBJECTIVES: Automated whole brain segmentation from magnetic resonance images is of great interest for the development of clinically relevant volumetric markers for various neurological diseases. Although deep learning methods have demonstrated remar...

Prediction of Lumbar Drainage-Related Meningitis Based on Supervised Machine Learning Algorithms.

Frontiers in public health
BACKGROUND: Lumbar drainage is widely used in the clinic; however, forecasting lumbar drainage-related meningitis (LDRM) is limited. We aimed to establish prediction models using supervised machine learning (ML) algorithms.

Research on Image Recognition of Gymnastics Sports Injuries Based on Deep Learning.

Computational intelligence and neuroscience
Gymnastics is an increasingly popular sport and an important event in the Olympic Games. However, the number of unavoidable injuries in sports is also increasing, and the treatment after the injury is very important. We reduce the harm caused by the ...

Human Behavior Recognition in Outdoor Sports Based on the Local Error Model and Convolutional Neural Network.

Computational intelligence and neuroscience
With the rapid development of the Internet, various electronic products based on computer vision play an increasingly important role in people's daily lives. As one of the important topics of computer vision, human action recognition has become the m...

Sales Forecast of Marketing Brand Based on BP Neural Network Model.

Computational intelligence and neuroscience
With the advancement of globalization, the market competition among enterprises has become increasingly intense. To win a good market, an enterprise must understand and grasp the laws of the market economy and accordingly predict the future of the ma...

Intelligent Analysis of Exercise Health Big Data Based on Deep Convolutional Neural Network.

Computational intelligence and neuroscience
In this paper, the algorithm of the deep convolutional neural network is used to conduct in-depth research and analysis of sports health big data, and an intelligent analysis system is designed for the practical process. A convolutional neural networ...

Deep Learning-Based Optimization Algorithm for Enterprise Personnel Identity Authentication.

Computational intelligence and neuroscience
Enterprise strategic management is not only an important part of enterprise work, but also an important factor to deepen the reform of management system and promote the centralized and unified management of enterprises. Enterprise strategic managemen...

HE-DFNETS: A Novel Hybrid Deep Learning Architecture for the Prediction of Potential Fishing Zone Areas in Indian Ocean Using Remote Sensing Images.

Computational intelligence and neuroscience
The Indian subcontinent is known for its larger coastline spanning, over 8100 km and is considered the habitat for many millions of people. The livelihood of their habitat is purely dependent upon the fishing activities. Often, the search for fish re...

Application of Human Posture Recognition Based on the Convolutional Neural Network in Physical Training Guidance.

Computational intelligence and neuroscience
The application of sports game video analysis in athlete training and competition analysis feedback has attracted extensive attention, but the traditional sports human body posture estimation method has a large error between the athlete's human body ...