333 Result(s)
within
Jian**n Chen
Computer Science
Artificial Intelligence
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Article
TAENet: transencoder-based all-in-one image enhancement with depth awareness
Recently, CNN-based all-in-one image enhancement methods have been proposed to solve multiple image degradation tasks. However, these CNN-based methods usually have two limitations. One limitation is that they...
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Article
Intercity customized passenger transportation service plan optimization design with spatial-temporal accessibility based on BIRCH-VNS
Traditional intercity passenger transportation is inefficient, inflexible, and financially unrewarding, failing to meet the demands of intercity travel. To address these issues, this study utilizes historical ...
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Article
Infrared tracking for accurate localization by capturing global context information
The existing model’s representation and fusion of features is inadequate in TIR scenarios. Our design of a new infrared tracking algorithm is based on this problem. Specifically, we use the transformer structu...
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Article
Open AccessImage Deblurring Using Feedback Mechanism and Dual Gated Attention Network
Recently, image deblurring task driven by the encoder-decoder network has made a tremendous amount of progress. However, these encoder-decoder-based networks still have two disadvantages: (1) due to the lack o...
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Article
Complex visual question answering based on uniform form and content
Complex visual question answering holds the potential to enhance artificial intelligence proficiency in understanding natural language, stimulate advances in computer vision technologies, and expand the range ...
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Article
FAformer: parallel Fourier-attention architectures benefits EEG-based affective computing with enhanced spatial information
The balance of brain functional segregation (i.e., the process in specialized local subsystems) and integration (i.e., the process in global cooperation of the subsystems) is crucial for cognition in human bei...
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Article
Open AccessInformation-Minimizing Generative Adversarial Network for Fair Generation and Classification
Studies show that machine learning models trained from biased data can discriminate against groups with certain sensitive attributes. This problem can be mitigated by cleaning the original data or learning fai...
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Chapter and Conference Paper
Removal of EOG Artifact in Electroencephalography with EEMD-ICA: A Semi-simulation Study on Identification of Artifactual Components
Purpose: The electroencephalography (EEG) signals recorded in clinical settings are usually corrupted by electrooculography (EOG) artifacts. EEMD-ICA is a commonly used method for removing EOG artifacts. This stu...
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Chapter and Conference Paper
FFANet: Dual Attention-Based Flow Field Aware Network for 3D Grid Classification and Segmentation
Deep learning-based approaches for three-dimensional (3D) grid understanding and processing tasks have been extensively studied in recent years. Despite the great success in various scenarios, the existing app...
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Chapter and Conference Paper
MARS: An Instance-Aware, Modular and Realistic Simulator for Autonomous Driving
Nowadays, autonomous cars can drive smoothly in ordinary cases, and it is widely recognized that realistic sensor simulation will play a critical role in solving remaining corner cases by simulating them. To t...
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Chapter and Conference Paper
Visual-Textual Attention for Tree-Based Handwritten Mathematical Expression Recognition
Handwritten mathematical expression recognition (HMER) has attracted much attention and achieved remarkable progress under the encoder-decoder framework. However, it is still challenging due to complex structu...
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Chapter and Conference Paper
ePoW Energy-Efficient Blockchain Consensus Algorithm for Decentralize Federated Learning System in Resource-Constrained UAV Swarm
With the proliferation of Unmanned Aerial Vehicles (UAV) and UAV swarms, there has been growing interest in using them for collaborative computing tasks. Blockchain-based Federated learning (BFL) is an excelle...
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Chapter and Conference Paper
Fake Comment Detection Based on Generative Adversarial Networks
Fake comments are a widespread problem in various online activities. This issue not only impacts the consumer experience and service quality but also makes it difficult to distinguish genuine information from ...
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Chapter and Conference Paper
Users’ Emotional Diffusion and Public Opinion Evolution Under Public Health Emergencies: Taking the Community Group Purchasing on Zhihu as an Example
COVID-19 closures forced community residents to organize daily supply group purchasing for anti-epidemic needs. Public service satisfaction constitutes an important public health emergency governance indicator...
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Chapter and Conference Paper
A Blockchain-Enabled Decentralized Federated Learning System with Transparent and Open Incentive and Audit Contracts
Federated learning is an innovative and secure artificial intelligence model that ensures distributed privacy protection. However, FL faces serious challenges such as potential single point failures, lack of t...
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Article
FFANet: dual attention-based flow field-aware network for wall identification
Deep learning-based approaches for understanding and analyzing 3D flow field grids have been extensively studied in recent years due to their importance in exploring the physical mechanisms of flow fields. How...
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Article
Select and calibrate the low-confidence: dual-channel consistency based graph convolutional networks
Although Graph Convolutional Networks (GCNs) have achieved excellent results in various graph-related tasks, their performance at low label rates is still unsatisfactory. Previous studies in Semi-Supervised Le...
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Article
EnNeRFACE: improving the generalization of face reenactment with adaptive ensemble neural radiance fields
Face reenactment is a critical technology of digital face editing. Lately, the NeRFACE, a face reenactment method based on neural radiance fields, has been proposed, making the reconstruction accuracy of the t...
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Article
SATFace: Subject Agnostic Talking Face Generation with Natural Head Movement
Talking face generation is widely used in education, entertainment, shop**, and other social practices. Existing methods focus on matching the speaker’s mouth shape with the speech content. Still, there is a...
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Article
A discriminative multiple-manifold network for image set classification
Because the distinct advantages of manifold-learning methods for feature extraction, Riemannian manifolds have been used extensively in image recognition tasks in recent years. However, large intra-class varia...
