AIMC Topic: Data Collection

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A Comparison on LSTM Deep Learning Method and Random Walk Model Used on Financial and Medical Applications: An Example in COVID-19 Development Prediction.

Computational intelligence and neuroscience Aug 23, 2022
This study aims to establish the model of the cryptocurrency price trend based on a financial theory using the Long Short-Term Memory (LSTM) networks model with multiple combinations between the window length and the predicting horizons. The Random W...
Humans Neural Networks, Computer COVID-19 Deep Learning Data Collection
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A data-centric weak supervised learning for highway traffic incident detection.

Accident; analysis and prevention Aug 19, 2022
Using the data from loop detector sensors for near-real-time detection of traffic incidents on highways is crucial to averting major traffic congestion. While recent supervised machine learning methods offer solutions to incident detection by leverag...
Humans Support Vector Machine Accidents, Traffic Supervised Machine Learning Data Collection
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How do providers of artificial intelligence (AI) solutions propose and legitimize the values of their solutions for supporting diagnostic radiology workflow? A technography study in 2021.

European radiology Aug 18, 2022
OBJECTIVES: How do providers of artificial intelligence (AI) solutions propose and legitimize the values of their solutions for supporting diagnostic radiology workflow?
Humans Artificial Intelligence Radiography Radiology Workflow Data Collection
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Data Augmentation for Deep-Learning-Based Multiclass Structural Damage Detection Using Limited Information.

Sensors (Basel, Switzerland) Aug 18, 2022
The deterioration of infrastructure's health has become more predominant on a global scale during the 21st century. Aging infrastructure as well as those structures damaged by natural disasters have prompted the research community to improve state-of...
Humans Neural Networks, Computer Databases, Factual Aging Deep Learning Data Collection
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Convolution neural network with batch normalization and inception-residual modules for Android malware classification.

Scientific reports Aug 17, 2022
Deep learning technology is changing the landscape of cybersecurity research, especially the study of large amounts of data. With the rapid growth in the number of malware, developing of an efficient and reliable method for classifying malware has be...
Neural Networks, Computer Machine Learning Algorithms Data Collection Computer Security
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GLD-Net: Deep Learning to Detect DDoS Attack via Topological and Traffic Feature Fusion.

Computational intelligence and neuroscience Aug 16, 2022
Distributed denial of service (DDoS) attacks are the most common means of cyberattacks against infrastructure, and detection is the first step in combating them. The current DDoS detection mainly uses the improvement or fusion of machine learning and...
Neural Networks, Computer Machine Learning Deep Learning Data Collection Information Systems
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Analysis of e-Mail Spam Detection Using a Novel Machine Learning-Based Hybrid Bagging Technique.

Computational intelligence and neuroscience Aug 9, 2022
e-mail service providers and consumers find it challenging to distinguish between spam and nonspam e-mails. The purpose of spammers is to spread false information by sending annoying messages that catch the attention of the public. Various spam ident...
Machine Learning Databases, Factual Data Collection Electronic Mail
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Risky-Driving-Image Recognition Based on Visual Attention Mechanism and Deep Learning.

Sensors (Basel, Switzerland) Aug 5, 2022
Risky driving behavior seriously affects the driver's ability to react, execute and judge, which is one of the major causes of traffic accidents. The timely and accurate identification of the driving status of drivers is particularly important, since...
Deep Learning Accidents, Traffic Data Collection Automobile Driving Recognition, Psychology
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A Lightweight CNN Model Based on GhostNet.

Computational intelligence and neuroscience Jul 31, 2022
The existing deep learning models have problems such as large weight parameters and slow inference speed of equipment. In practical applications such as fire detection, they often cannot be deployed on equipment with limited resources due to the huge...
Neural Networks, Computer Algorithms Fires Data Collection
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A dynamic AES cryptosystem based on memristive neural network.

Scientific reports Jul 28, 2022
This paper proposes an advanced encryption standard (AES) cryptosystem based on memristive neural network. A memristive chaotic neural network is constructed by using the nonlinear characteristics of a memristor. A chaotic sequence, which is sensitiv...
Neural Networks, Computer Algorithms Data Collection Computer Security
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