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Intelligent Information Processing XII: 13th IFIP TC 12 International Conference, IIP 2024, Shenzhen, China, May 36, 2024, Proceedings, Part II 2024 ed. [Hardback]

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  • Formāts: Hardback, 207 pages, height x width: 235x155 mm, 65 Illustrations, color; 8 Illustrations, black and white; XXX, 207 p. 73 illus., 65 illus. in color., 1 Hardback
  • Sērija : IFIP Advances in Information and Communication Technology 704
  • Izdošanas datums: 18-Apr-2024
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031579186
  • ISBN-13: 9783031579189
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Intelligent Information Processing XII: 13th IFIP TC 12 International Conference, IIP 2024, Shenzhen, China, May 36, 2024, Proceedings, Part II 2024 ed.
  • Formāts: Hardback, 207 pages, height x width: 235x155 mm, 65 Illustrations, color; 8 Illustrations, black and white; XXX, 207 p. 73 illus., 65 illus. in color., 1 Hardback
  • Sērija : IFIP Advances in Information and Communication Technology 704
  • Izdošanas datums: 18-Apr-2024
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031579186
  • ISBN-13: 9783031579189
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783031579189.html
Keywords:
The two-volume set IFIP AICT 703 and 704 constitutes the refereed conference proceedings of the 13th IFIP TC 12 International Conference on Intelligent Information Processing XII, IIP 2024, held in Shenzhen, China, during May 3–6, 2024. 

The 49 full papers and 5 short papers presented in these proceedings were carefully reviewed and selected from 58 submissions. 
The papers are organized in the following topical sections: 

Volume I: Machine Learning; Natural Language Processing; Neural and Evolutionary Computing; Recommendation and Social Computing; Business Intelligence and Risk Control; and Pattern Recognition.

Volume II: Image Understanding.
.- Early Anomaly Detection in Hydraulic Pumps Based on LSTM Traffic
Prediction Model.



.- Dynamic Parameter Estimation for Mixtures of Plackett-Luce Models.



.- Recognition of Signal Modulation Pattern Based on Multi-Task
Self-Supervised Learning.



.- Dependency-Type Weighted Graph Convolutional Network on End-to-End
Aspect-Based Sentiment Analysis.



.- Utilizing Attention for Continuous Human Action Recognition Based on
Multimodal Fusion of Visual and Inertial.



.- HARFMR: Human Activity Recognition with Feature Masking and
Reconstruction.



.- CAPPIMU: A Composite Activities Dataset for Human Activity Recognition
Utilizing Plantar Pressure and IMU Sensors.



.- Open-Set Sensor Human Activity Recognition Based on Reciprocal Time
Series.



.- Image Understanding.



.- A Concept-Based Local Interpretable Model-agnostic Explanation Approach
for Deep Neural Networks in Image Classification.



.- A Deep Neural Network-based Segmentation Method for Multimodal Brain Tumor
Images.



.- Graph Convolutional Networks for Predicting Mechanical Characteristics of
3D Lattice Structures.



.- 3D Object Reconstruction with Deep Learning.



.- Adaptive Prototype Triplet Loss for Cross-Resolution Face Recognition.



.- Hand Gesture Recognition Using a Multi-modal Deep Neural Network.