AIMC Topic: Pattern Recognition, Automated

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Construction of Knowledge Graph English Online Homework Evaluation System Based on Multimodal Neural Network Feature Extraction.

Computational intelligence and neuroscience
This paper defines the data schema of the multimodal knowledge graph, that is, the definition of entity types and relationships between entities. The knowledge point entities are defined as three types of structures, algorithms, and related terms, sp...

Visualization and Analysis Model of Industrial Economy Status and Development Based on Knowledge Graph and Deep Neural Network.

Computational intelligence and neuroscience
This paper adopts knowledge mapping combined with a deep neural network algorithm to conduct in-depth research and analysis on the current situation and development of the industrial economy and designs a visual analysis model of economic development...

Adversarial Attack on Skeleton-Based Human Action Recognition.

IEEE transactions on neural networks and learning systems
Deep learning models achieve impressive performance for skeleton-based human action recognition. Graph convolutional networks (GCNs) are particularly suitable for this task due to the graph-structured nature of skeleton data. However, the robustness ...

Combining biomedical knowledge graphs and text to improve predictions for drug-target interactions and drug-indications.

PeerJ
Biomedical knowledge is represented in structured databases and published in biomedical literature, and different computational approaches have been developed to exploit each type of information in predictive models. However, the information in struc...

A union of deep learning and swarm-based optimization for 3D human action recognition.

Scientific reports
Human Action Recognition (HAR) is a popular area of research in computer vision due to its wide range of applications such as surveillance, health care, and gaming, etc. Action recognition based on 3D skeleton data allows simplistic, cost-efficient m...

FoSSA Optimization-Based SVM Classifier for the Recognition of Partial Discharge Patterns in HV Cables.

Computational intelligence and neuroscience
In order to enhance the classification accuracy and the generalization performance of the SVM classifier in cable partial discharge (PD) pattern recognition, a firefly optimized sparrow search algorithm (FoSSA) is proposed to optimize its kernel func...

Discriminative Transfer Learning for Driving Pattern Recognition in Unlabeled Scenes.

IEEE transactions on cybernetics
Driving pattern recognition based on features, such as GPS, gear, and speed information, is essential to develop intelligent transportation systems. However, it is usually expensive and labor intensive to collect a large amount of labeled driving dat...

Explaining the differences of gait patterns between high and low-mileage runners with machine learning.

Scientific reports
Running gait patterns have implications for revealing the causes of injuries between higher-mileage runners and low-mileage runners. However, there is limited research on the possible relationships between running gait patterns and weekly running mil...

Internet of Things with Deep Learning-Based Face Recognition Approach for Authentication in Control Medical Systems.

Computational and mathematical methods in medicine
Internet of Things (IoT) with deep learning (DL) is drastically growing and plays a significant role in many applications, including medical and healthcare systems. It can help users in this field get an advantage in terms of enhanced touchless authe...

Classifying neovascular age-related macular degeneration with a deep convolutional neural network based on optical coherence tomography images.

Scientific reports
Neovascular age-related macular degeneration (nAMD) is among the main causes of visual impairment worldwide. We built a deep learning model to distinguish the subtypes of nAMD using spectral domain optical coherence tomography (SD-OCT) images. Data f...