LEADER 12368nam 22006615 450 001 9910845498603321 005 20240322120353.0 010 $a981-9975-45-X 024 7 $a10.1007/978-981-99-7545-7 035 $a(CKB)31136227700041 035 $a(DE-He213)978-981-99-7545-7 035 $a(MiAaPQ)EBC31229843 035 $a(Au-PeEL)EBL31229843 035 $a(EXLCZ)9931136227700041 100 $a20240322d2024 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial Intelligence in China$b[electronic resource] $eProceedings of the 5th International Conference on Artificial Intelligence in China /$fedited by Wei Wang, Jiasong Mu, Xin Liu, Zhenyu Na Na 205 $a1st ed. 2024. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2024. 215 $a1 online resource (X, 635 p. 258 illus., 204 illus. in color.) 225 1 $aLecture Notes in Electrical Engineering,$x1876-1119 ;$v1043 311 $a981-9975-44-1 327 $aIntro -- Contents -- Research on Deep Learning Operator Testing of Intelligent Software Based on Fuzz Testing Technology -- 1 Overview -- 2 Deep Learning Framework and Operator Library -- 3 Deep Learning Operator Testing -- 3.1 Problems and Cause Analysis of the Accuracy of Deep Learning Operators -- 3.2 Differential Testing -- 3.3 Guided Fuzz Testing -- 4 Testing Design of Deep Learning Operator Based on Differential Fuzz Testing -- 5 Summary and Outlook -- References -- Computer Aided System Design for Handwriting Identification Based on Imaging -- 1 Introduction -- 2 Dataset Establishment and System Design -- 2.1 Dataset -- 2.2 Model -- 3 Experiment and Result Analysis -- 4 Conclusion -- References -- Dynamic Optimization Deployment of Wireless Sensor Networks Based on TPWRLS Graph Construction and VFA -- 1 Introduction -- 2 Mobile Node Selection Based on TPWRLS Graph Construction -- 2.1 TPWRLS Graph Construction -- 2.2 Mobile Node Selection -- 3 Node Movement Based on VFA -- 3.1 VFA -- 3.2 Standard for Evaluation -- 4 Experiment and Analysis -- 4.1 Experiment on Selecting the Number of Mobile Nodes -- 4.2 Iterative Experiment of VFA -- 5 Conclusion -- References -- Research Review on Application of Genetic Algorithms for Multi-Objective Optimal Management of Building Construction -- 1 Introduction -- 2 Emergence and Application of Genetic Algorithms -- 2.1 Emergence of Genetic Algorithms -- 2.2 Research Timeline -- 2.3 Multi-Objective Optimal Management -- 2.4 Parameter Coding Methods -- 3 Summary -- References -- AgsNet: An Attention-Guided Lightweight Segmentation Network -- 1 Introduction -- 2 Materials and Method -- 2.1 Research Subjects -- 2.2 Proposed Model -- 2.3 Bayesian Classifier -- 2.4 Attention Mechanism -- 3 Experiment -- 3.1 Data Preprocessing and Augmentation -- 3.2 Implementation Details -- 3.3 Results -- 3.4 Conclusion. 327 $aReferences -- A TDOA-Based Optimization Method for Staircase Area Positioning -- 1 Introduction -- 2 Base Station Deployment in the Staircase Area -- 3 The Method of Stair Area Localization Based on TDOA Algorithm -- 4 Conclusion -- References -- Design and Implementation of Intelligent Classified Garbage Bin -- 1 Introduction -- 2 Garbage Classification Recognition -- 2.1 Introduction to GhostNet -- 2.2 Transfer Learning for Recognition Model Training -- 2.3 Preparation of Datasets -- 2.4 Training and Result Analysis -- 3 Hardware Connection and Implementation -- 3.1 System Design Goals -- 4 GUI Design -- 4.1 Boot Interface -- 4.2 Main Interface -- 4.3 Detection Interface -- 5 Summary -- References -- Knowledge-Enhanced Recommendation System Design for Mechatronics IoT Cloud Platform -- 1 Introduction -- 2 Related Work -- 2.1 Internet of Things -- 2.2 Cloud Technology -- 2.3 Knowledge Graph -- 3 Mechatronics Internet of Things Cloud Service System Design -- 3.1 Mechatronics Internet of Things Cloud Service Platform Architecture -- 3.2 Knowledge-Enhanced Platform Recommendation Algorithm Service -- 4 Key Technologies -- 4.1 Platform Service Mode Based on Cloud Technology -- 4.2 Scene Analysis and Object Relationship Prediction -- 4.3 Multi-hop Cross-Modal Attention Layer -- 4.4 Experimental Result -- 5 Conclusion -- References -- Aspect-Level Sentiment Analysis by Fusing Local Information with Graph Attention Networks -- 1 Introduction -- 2 LSI-RGAT Network Model Construction -- 2.1 Word Embedding Layer -- 2.2 Syntax-Aware Layer -- 3 Experiment -- 3.1 Data Set and Experimental Setup -- 3.2 Analysis of Experimental Results -- 4 Conclusion -- References -- Image Segmentation Algorithm Based on Improved U-Net for Mineral Froth Flotation Process -- 1 Introduction -- 2 Proposed Method -- 2.1 Attention Module -- 2.2 ASPP Head -- 3 Experiments and Analysis. 327 $a3.1 Datasets and Experiment Setup Details -- 3.2 Evaluation Criteria -- 3.3 Comparison with SOTA Works -- 4 Conclusion -- References -- Automatic Summarization Research for Long Texts Targeting Think Tanks -- 1 Introduction -- 2 Literature Review -- 2.1 Extractive Summarization -- 2.2 Abstractive Summarization -- 3 Dataset -- 4 Method -- 4.1 Candidate Sentence Extraction Module -- 4.2 Pre-trained Generation Module -- 4.3 Beam Search Module -- 4.4 AELoss -- 5 Experiments and Analysis of Results -- 5.1 Experimental Design -- 5.2 Comparative Experiment -- 5.3 Analysis of Experimental Results -- 6 Conclusion -- References -- Research on Semantic Segmentation Algorithm for Autonomous Driving Based on Improved DeepLabv3+ -- 1 Introduction -- 2 RS-DeepLab Model -- 2.1 Model Network Structure -- 2.2 Backbone Network -- 2.3 ARMS Architecture -- 2.4 FFMS Architecture -- 3 Experiment and Analysis -- 3.1 Experimental Configuration -- 3.2 Evaluation Metrics -- 3.3 Model Segmentation Results -- 3.4 Model Improvement Experiment -- 4 Conclusion -- References -- Joint Security Protection and Transmission Delay Scheduling Scheme of Voice Switching Network -- 1 Introduction -- 2 System Model -- 2.1 Encryption -- 2.2 System Architecture -- 2.3 Constraints -- 2.4 Delay Formulation -- 3 Mechanism Model -- 3.1 Encryption -- 3.2 Adjust HTS Flows Sampling Period -- 3.3 AVB Flows Planning -- 4 Simulations and Results -- 4.1 Experimental Data -- 4.2 Analysis -- 5 Conclusion -- References -- Subway Tunnel Segment Disease Detection System Based on Machine Vision Technology -- 1 Introduction -- 2 Overall Design -- 3 Hardware System Design -- 3.1 Line Scan Integrated Camera Device -- 3.2 Image Acquisition Card -- 3.3 Industrial Computer -- 4 Software System Design -- 5 Experimental Results -- 6 Conclusions -- References. 327 $aDevice-Free Cross-Environment Human Action Recognition Using Wi-Fi Signals -- 1 Introduction -- 2 Methodology -- 2.1 Overview -- 2.2 Data Preprocessing -- 2.3 Action Recognition -- 3 IMPLEMENTATION and EVALUATION -- 3.1 Experimental Setup -- 3.2 Evaluation -- 4 Conclusion -- References -- The Performance Analysis of Double Intelligent Reflecting Surface-Assisted Cognitive Radio Network -- 1 Introduction -- 2 System Model and Problem Formulation -- 2.1 System Model -- 2.2 Problem Formulation -- 3 Proposed Solution to (P1) -- 3.1 Optimizing Transmit Beamforming -- 3.2 Optimizing the Reflection Coefficients -- 4 Summary of the AO Algorithm -- 5 Simulation Results -- 5.1 Simulation Scenario -- 5.2 Performance Evaluation -- 6 Conclusion -- References -- A Novel Point Cloud Completion Method Based on Height Map and Dual-Mask Images -- 1 Introduction -- 2 An Image Inpainting Method for Point Cloud Height Map Based on Dual-Mask Images -- 2.1 Acquisition of Point Cloud Height Map -- 2.2 Spatial Distribution Characteristics of Hollow Pixels -- 2.3 Dual-Mask Hole Filling Method for Pixel Completion -- 3 Experiment -- 4 Summary -- References -- Deep Learning for Skin Lesion Segmentation: A Review and Outlook -- 1 Introduction -- 1.1 Contribution of Current Work -- 2 Deep Learning Methods -- 2.1 Deep Neural Network Segmentation Architectures -- 2.2 Techniques for Skin Lesion Segmentation -- 3 Discussion and Outlook -- 3.1 Main Challenges -- 3.2 Trends in the Segmentation Methods -- 4 Conclusion -- References -- Research on Revenue Prediction of Automobile Manufacturing Enterprises -- 1 Introduction -- 2 Methodology -- 3 Experiment and Analysis -- 3.1 Industry Sales Prediction Based on RF and SARIMA -- 3.2 Enterprises Revenue Prediction Based on CNN -- 3.3 Benchmark Model-Based on Random Forest -- 4 Conclusion and Future Works -- References. 327 $aCoal Mine Risk Classification Prediction Model Based on BERT -- 1 Introduction -- 2 System Model -- 2.1 Network Architectures -- 2.2 Design of the Loss Module -- 2.3 Design of the Save Module -- 3 Experiment and Analysis -- 3.1 Data Preparation -- 3.2 ALBERT Module -- 3.3 TextCNN Module -- 3.4 Fully Connected Layer -- 3.5 Output Labels -- 3.6 Experimental Results -- 4 Conclusion and Future Works -- 4.1 Conclusion -- 4.2 Future Works -- References -- Research on Construction and Application of Knowledge Graph for Coal Mine Safety Production Specifications -- 1 Introduction -- 2 Review of Literature -- 2.1 Coal Mine Safety Production Specifications -- 2.2 Knowledge Graph and Application -- 3 Knowledge Graph Construction -- 3.1 Data Description and Processing -- 3.2 Designing the Ontology Structure -- 3.3 Ontology Construction -- 3.4 Knowledge Extraction -- 3.5 Constructing the Graph -- 4 Application -- 4.1 Topic Analysis -- 4.2 Knowledge Association Analysis -- 5 Conclusion -- References -- A TMFV-Based Adaptive E-Learning System for Generating and Allocating Questions -- 1 Introduction -- 2 Methodology -- 2.1 Adaptation Module Framework -- 2.2 Adaptive Question Generation -- 2.3 Dynamic Knowledge Tracking -- 3 Experiments -- 3.1 Datasets -- 3.2 Results -- 4 Conclusions -- References -- MedFPNet: A Medical Image Segmentation Network Based on Fourier Transform -- 1 Introduction -- 2 Related Work -- 2.1 Convolutional Neural Networks (CNNs) -- 2.2 Fourier Transform -- 3 Method -- 3.1 Overall Model -- 3.2 The Coarse and the Fine Double Branches -- 3.3 Residual Amplitude Block, Residual Phase Block -- 4 Experiments and Results -- 4.1 Dataset and Experimental Details -- 4.2 Experimental Results -- 5 Conclusion -- References -- Image Classification Algorithm Based on Improved Soft Thresholding and Residual Network -- 1 Introduction. 327 $a2 ST-ResNet18 Model Structure. 330 $aThis book brings together papers presented at the 2023 The International Conference on Artificial Intelligence in China (ChinaAI), which provides a venue to disseminate the latest developments and to discuss the interactions and links between these multidisciplinary fields. Spanning topics covering all topics in Artificial Intelligence with new development in China, this book is aimed at undergraduate and graduate students in Electrical Engineering, Computer Science and Mathematics, researchers and engineers from academia and industry as well as government employees (such as NSF, DOD, DOE). 410 0$aLecture Notes in Electrical Engineering,$x1876-1119 ;$v1043 606 $aArtificial intelligence 606 $aNeural networks (Computer science) 606 $aComputer vision 606 $aArtificial Intelligence 606 $aMathematical Models of Cognitive Processes and Neural Networks 606 $aComputer Vision 615 0$aArtificial intelligence. 615 0$aNeural networks (Computer science). 615 0$aComputer vision. 615 14$aArtificial Intelligence. 615 24$aMathematical Models of Cognitive Processes and Neural Networks. 615 24$aComputer Vision. 676 $a006.3 702 $aWang$b Wei$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMu$b Jiasong$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aLiu$b Xin$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aNa$b Zhenyu Na$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910845498603321 996 $aArtificial Intelligence in China$92025640 997 $aUNINA