AIMC Topic: Algorithms

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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...

Research on Online Social Network Information Leakage-Tracking Algorithm Based on Deep Learning.

Computational intelligence and neuroscience
The rapid iteration of information technology makes the development of online social networks increasingly rapid, and its corresponding network scale is also increasingly large and complex. The corresponding algorithms to deal with social networks an...

Simulation of English Word Order Sorting Based on Semionline Model and Artificial Intelligence.

Computational intelligence and neuroscience
To improve the word order ranking effect of English language retrieval, based on machine learning algorithms, this paper combines a semionline model to construct an artificial intelligence ranking model for English word order based on a semionline mo...

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...

Deep Learning-Based Real-Time Discriminate Correlation Analysis for Breast Cancer Detection.

BioMed research international
Breast cancer is the most common cancer in women, and the breast mass recognition model can effectively assist doctors in clinical diagnosis. However, the scarcity of medical image samples makes the recognition model prone to overfitting. A breast ma...

Self-Adaptation Resource Allocation for Continuous Offloading Tasks in Pervasive Computing.

Computational and mathematical methods in medicine
Advancement in technology has led to an increase in data. Consequently, techniques such as deep learning and artificial intelligence which are used in deciphering data are increasingly becoming popular. Further, advancement in technology does increas...

Active learning of causal structures with deep reinforcement learning.

Neural networks : the official journal of the International Neural Network Society
We study the problem of experiment design to learn causal structures from interventional data. We consider an active learning setting in which the experimenter decides to intervene on one of the variables in the system in each step and uses the resul...

Machine learning in the identification, prediction and exploration of environmental toxicology: Challenges and perspectives.

Journal of hazardous materials
Over the past few decades, data-driven machine learning (ML) has distinguished itself from hypothesis-driven studies and has recently received much attention in environmental toxicology. However, the use of ML in environmental toxicology remains in t...

The minimum regret path problem on stochastic fuzzy time-varying networks.

Neural networks : the official journal of the International Neural Network Society
In this paper, we introduce a stochastic fuzzy time-varying minimum regret path problem (SFTMRP), which combines the characteristics of the min-max regret path and maximum probability path as a variant of the stochastic fuzzy time-varying shortest pa...