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Record Nr. |
UNINA9910920446203321 |
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Autore |
Yu Haipeng |
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Titolo |
Computer Applications : 39th CCF National Conference of Computer Applications, CCF NCCA 2024, Harbin, China, July 15–18, 2024, Proceedings, Part II / / edited by Chengtao Cai, Haipeng Yu, Lan Huang, Weipeng Jing, Xuebin Chen, Xianhua Song, Zeguang Lu |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (361 pages) |
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Collana |
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Communications in Computer and Information Science, , 1865-0937 ; ; 2275 |
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Altri autori (Persone) |
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CaiChengtao |
HuangLan |
JingWeipeng |
ChenXuebin |
SongXianhua |
LuZeguang |
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Disciplina |
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Soggetti |
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Computational intelligence |
Application software |
Artificial intelligence |
Computer networks |
Computer systems |
Computational Intelligence |
Computer and Information Systems Applications |
Artificial Intelligence |
Computer Communication Networks |
Computer System Implementation |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Pattern Recognition & Machine Learning -- YOLOv5s Multimode Sensing Based Pipe Network Detection and Inspection Method -- Automatic Analysis Framework for Campus Wireless Network Performance Based on Web Services and Supervised Learning Methods |
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-- Learning to Score Sign Language with Two Stage Method -- A Lightweight Dual Path Conformer Network for Speech Separation -- SLPNet Student Learning Performance Prediction During the COVID19 Pandemic Via a Deep Neural Network -- A Rapid Finger Vein Recognition Approach Based on UNet -- A Surface Defect Detection Method Based on Domain Correlation -- FDA UNet Frequency Domain Dual Attention Based on UNet for Stain Normalization -- A DQN Based Resource Adaptation Strategy for In Network Computing Based Holographic Type Communication -- Local Multiscale Aggregation with a Global Attention Super Resolution Network -- An Adaptive Capsule Network Based on 3D Convolution Based Attention -- A Comprehensive Attention Scoring Model for Collaborative Learning -- Network Communication and Security -- Analysis of the Influence of Multi Point Pumping on the Gain in an Optical Fiber Amplifier -- Exploring the Feasibility of Raspberry Pi 4 Model B Clusters as an Alternative to Advanced Process Chip Computers -- Internal Task Offloading Deployment Mechanism of In Network Computing Devices for Holographic Type Communication -- A Review of Research on Vehicle CAN Network Intrusion Detection via Artificial Intelligence -- IEN NFT A Naming Based Novel Semantic NFT Architeture with Intrinsic Binding and Flexible Interoperability -- Frontier and Comprehensive Applications -- From DPI Data to Warning Real Time Risk Assessment in the Fight Against Internet Fraud -- Information Propagation Model Based on 2 Dimensional Simplicial Complexes -- Quantitative Evaluation of the Whitening Effects of Facial Masks via EfficientNet and the Wavelet Transform -- Data Science and Technology -- FabricDG A Transaction Conflict Optimization Solution for the Consortium Blockchain -- Multivariate Time Series Forecasting of Integrated Energy Systems Based on Fast Fourier Transform Fully Connected Space Time Graph -- Automobile Parts Detection and Traceability Based on Blockchain and Federated Learning -- Research on Traceability Encryption of Auto Parts Based on Blockchain and IBE -- An Efficient Method for Encrypting and Protecting Electricity Usage Privacy Data. |
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Sommario/riassunto |
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This two-volume set, CCIS 2274 and CCIS 2275, constitutes the refereed proceedings of the 39th National Conference on China Computer Federation, CCF NCCA 2024, held in Harbin, China, during July 15–18, 2024. The 48 full papers presented here were carefully reviewed and selected from 238 submissions. These papers are organized in the following topical sections: Part I: Artificial Intelligence and Applications; Data Science and Technology. Part II: Pattern Recognition & Machine Learning; Network Communication and Security; Frontier and Comprehensive Applications; Data Science and Technology. |
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