544 Result(s)
within
English
Artificial Intelligence
Image Processing and Computer Vision
**-**a Ding
Chapter
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Chapter and Conference Paper
Device-Free Cross-Environment Human Action Recognition Using Wi-Fi Signals
The research of human action recognition (HAR) based on Wi-Fi signals shows great application value in fields of human-computer interaction. However, many existing Wi-Fi-based HAR systems are vulnerable to env...
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Chapter and Conference Paper
Integrating Human Parsing and Pose Network for Human Action Recognition
Human skeletons and RGB sequences are both widely-adopted input modalities for human action recognition. However, skeletons lack appearance features and color data suffer large amount of irrelevant depiction. ...
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Chapter and Conference Paper
Research on Fault Diagnosis of Surge Arresters Based on Support Vector Recurrent Neural Network
Surge arresters are crucial protective components within electrical power systems, and the proper functioning is vital for the safety and reliability of the entire system. However, due to factors such as prolo...
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Chapter and Conference Paper
An Analysis of the Generalized Tit-for-Tat Strategy Within the Framework of Memory-One Strategies
The Tit-for-tat strategy is a traditional strategy in game theory. In the Prisoner’s Dilemma, the TFT strategy has been proven to be strong. However, within a four-component Memory-One strategy framework, the ...
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Chapter and Conference Paper
A Novel Method Based on Particle Swarm Optimization Support Vector Neural Network for Transformer Fault Diagnosis
In order to solve the issue of low accuracy in transformer fault diagnosis, a novel method based on particle swarm optimization support vector neural network (PSO-SVNN) is proposed in this paper. Firstly, the ...
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Chapter and Conference Paper
Swin-MMC: Swin-Based Model for Myopic Maculopathy Classification in Fundus Images
Myopic maculopathy is a highly myopic retinal disorder that often occurs in highly myopic patients, serving as a major cause of visual impairment and blindness in numerous countries. Currently, fundus images s...
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Chapter and Conference Paper
A Reinforcement Learning Approach for Personalized Diversity in Feeds Recommendation
Feeds recommendation has been widely used in various applications, such as e-commerce site, where users can constantly browse products generated by never-ending feeds. It’s important to not only consider insta...
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Chapter and Conference Paper
Mining Label Distribution Drift in Unsupervised Domain Adaptation
Unsupervised domain adaptation targets to transfer task-related knowledge from labeled source domain to unlabeled target domain. Although tremendous efforts have been made to minimize domain divergence, most e...
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Chapter and Conference Paper
Deformable CNN with Position Encoding for Arbitrary-Scale Super-Resolution
Implicit neural representation (INR) has been widely used to learn continuous representation of images, as it enables arbitrary-scale super-resolution (SR). However, most existing INR-based arbitrary-scale SR ...
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Chapter and Conference Paper
GAN-Based Image Compression with Improved RDO Process
GAN-based image compression schemes have shown remarkable progress lately due to their high perceptual quality at low bit rates. However, there are two main issues, including 1) the reconstructed image percept...
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Chapter and Conference Paper
Dual Fusion Network for Hyperspectral Semantic Segmentation
With the development of imaging technology, it becomes increasingly easy to obtain hyperspectral images (HSI) containing rich spectral information. The application of hyperspectral images in autonomous driving...
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Chapter and Conference Paper
A Hybrid Intelligent Model SFAHP-ANFIS-PSO for Technical Capability Evaluation of Manufacturing Enterprises
In the collaborative production environment of manufacturing tasks, the evaluation of enterprise technical capability in advance has a direct impact on the high-performance collaboration between the supplier a...
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Chapter and Conference Paper
Multimodal Controller for Generative Models
Class-conditional generative models are crucial tools for data generation from user-specified class labels. Existing approaches for class-conditional generative models require nontrivial modifications of backb...
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Chapter and Conference Paper
A Method for Identifying the Timeliness of Manufacturing Data Based on Weighted Timeliness Graph
Timeliness is one of the important indicators of data quality. In industrial production processes, a large amount of dependent data is generated, often resulting in unclear timestamps. Therefore, this article ...
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Chapter and Conference Paper
Small Temperature is All You Need for Differentiable Architecture Search
Differentiable architecture search (DARTS) yields highly efficient gradient-based neural architecture search (NAS) by relaxing the discrete operation selection to optimize continuous architecture parameters th...
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Chapter and Conference Paper
Graph Convolutional Neural Network Based on Channel Graph Fusion for EEG Emotion Recognition
To represent the unstructured relationships among EEG channels, graph neural networks are proposed to classify EEG signal. Currently most graph neural networks learn the relationships between EEG channels usin...
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Chapter and Conference Paper
A Novel Homogenized Chaotic System of Compressed Sensing Image Encryption Algorithm
Aimed at the problems of limited range, uneven distribution, and insufficient complexity of traditional one-dimensional chaotic map**. In this paper, a method for constructing chaotic measurement matrices is...
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Chapter and Conference Paper
Graph Contrastive Learning with Hybrid Noise Augmentation for Recommendation
Recommendation System is one of the effective tools to solve the problem of information overload in the era of big data, but the data sparsity has greatly affected its performance. Recently, contrastive learni...
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Chapter and Conference Paper
Sequential Seeding Initialization for SNIC Superpixels
In this paper, a novel seeding initialization strategy is introduced to simple non-iterative clustering (SNIC) superpixels for further optimizing the performance. First, half the total seeds are initialized on...
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Chapter and Conference Paper
Graph Fusion Multimodal Named Entity Recognition Based on Auxiliary Relation Enhancement
Multimodal Named Entity Recognition (MNER) aims to use images to locate and classify named entities in a given free text. The mainstream MNER method based on a pre-trained model ignores the syntactic relations...
