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Article
Exploring the effect of stress arousal on the positive emotional design of multimedia learning
Positive emotional design has been shown to have an important impact on multimedia learning. However, before learning multimedia materials, students may inevitably be stressed by external factors such as learn...
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Article
Adaptive discontinuous Galerkin finite element methods for the Allen-Cahn equation on polygonal meshes
In this paper, we develop a polygonal mesh adaptation algorithm for a fully implicit scheme based on discontinuous Galerkin (DG) finite element methods in space and backward Euler method in time to solve the A...
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Article
A survey of multi-source image fusion
Multi-source image fusion has become an important and useful new technology in the image understanding and computer vision fields. The purpose of multi-source image fusion is to intelligently synthesize image ...
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Chapter and Conference Paper
An Improved Prototypical Network for Endoscopic Grading of Intestinal Metaplasia
Intestinal metaplasia (IM) is confirmed to be the commonest symptom of early gastric cancer. IM grading by endoscopic images is essential to reduce the risk and mortality of gastric cancer. However, expensive ...
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Chapter and Conference Paper
DSQA-LLM: Domain-Specific Intelligent Question Answering Based on Large Language Model
Question Answering (QA) is crucial for humans to access vast knowledge bases, but there is a lack of attention towards representing raw, unstructured questions and answers in specific fields. Additionally, the...
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Chapter and Conference Paper
Spatially-Aware Human-Object Interaction Detection with Cross-Modal Enhancement
We propose a novel two-stage HOI detection model that incorporates cross-modal spatial information awareness. Human-object relative spatial relationships are highly relevant for specific HOI species, but curre...
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Article
Open AccessA Review and Outlook on Predictive Cruise Control of Vehicles and Typical Applications Under Cloud Control System
With the application of mobile communication technology in the automotive industry, intelligent connected vehicles equipped with communication and sensing devices have been rapidly promoted. The road and traff...
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Article
Miss-gradient boosting regression tree: a novel approach to imputing water treatment data
Complete data on wastewater quality are essential for managing and monitoring wastewater treatment processes. Most management and monitoring methods involve the use of voluminous training data for imputation, ...
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Article
AE-FPN: adaptive enhance feature learning for detecting wire defects
Wire defects usually occur in high-altitude transmission lines, leading to line transmission failures and even the possibility of large-scale power outages. Therefore, timely and accurate locating wire defects...
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Article
STSNet: a novel spatio-temporal-spectral network for subject-independent EEG-based emotion recognition
How to use the characteristics of EEG signals to obtain more complementary and discriminative data representation is an issue in EEG-based emotion recognition. Many studies have tried spatio-temporal or spatio...
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Article
Open AccessMeasuring cognitive load of digital interface combining event-related potential and BubbleView
Helmet mounted display systems (HMDs) are high-performance display devices for modern aircraft. We propose a novel method combining event-related potentials (ERPs) and BubbleView to measure cognitive load unde...
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Article
An effective pest detection method with automatic data augmentation strategy in the agricultural field
Currently, computer vision technology has been applied to detect and recognize pests for integrated pest management (IPM). Recent studies have shown that the accuracy of pest detection and recognition has been...
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Article
Open AccessWavelet transforms based ARIMA-XGBoost hybrid method for layer actions response time prediction of cloud GIS services
Layer actions response time is a critical indicator of cloud geographical information services (cloud GIS Services), which is of great significance to resource allocation and schedule optimization. However, si...
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Chapter and Conference Paper
A Unified Deep-Learning-Based Framework for Cochlear Implant Electrode Array Localization
Cochlear implants (CIs) are neuroprosthetics that can provide a sense of sound to people with severe-to-profound hearing loss. A CI contains an electrode array (EA) that is threaded into the cochlea during sur...
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Chapter and Conference Paper
Measuring Decision Confidence Levels from EEG Using a Spectral-Spatial-Temporal Adaptive Graph Convolutional Neural Network
Decision confidence can reflect the correctness of people’s decisions to some extent. To measure the reliability of human decisions in an objective way, we introduce a spectral-spatial-temporal adaptive graph ...
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Chapter and Conference Paper
SFusion: Self-attention Based N-to-One Multimodal Fusion Block
People perceive the world with different senses, such as sight, hearing, smell, and touch. Processing and fusing information from multiple modalities enables Artificial Intelligence to understand the world aro...
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Chapter and Conference Paper
Evaluating Rule-Based Global XAI Malware Detection Methods
In recent years explainable artificial intelligence (XAI) methods have been applied for interpreting machine learning-based Android malware detection approaches. XAI methods are capable of providing Android ma...
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Article
FVAE: a regularized variational autoencoder using the Fisher criterion
As a deep generative model, the variational autoencoder (VAE) is widely applied to solve problems of insufficient samples and imbalanced labels. In the VAE, the distribution of latent variables affects the qua...
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Article
Short text matching model with multiway semantic interaction based on multi-granularity semantic embedding
Short text matching is a fundamental technique of natural language processing. It plays an important role in information retrieval, question answering and paraphrase identification, etc. However, due to the la...
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Article
Graph convolutional networks and LSTM for first-person multimodal hand action recognition
Graph convolutional networks (GCNs) have been successfully introduced in skeleton-based human action recognition. Both human skeletons and hand skeletons are composed of open-loop chains, and each chain is com...
