Advances in Data Clustering
portes grátis
Advances in Data Clustering
Theory and Applications
Dornaika, Fadi; Vinh, Truong Hoang; Constantin, Joseph; Hamad, Denis
Springer Verlag, Singapore
01/2025
200
Dura
9789819776788
Pré-lançamento - envio 15 a 20 dias após a sua edição
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Chapter 1 Classification of Gougerot-Sjoegren syndrome Based on Artificial Intelligence.- Chapter 2 Deep learning Classification of Venous Thromboembolism based on Ultrasound imaging.- Chapter 3 Synchronization-Driven Community Detection: Dynamic Frequency Tuning Approach.- Chapter 4 Automatic Evolutionary Clustering for Human Activity Discovery.- Chapter 5 Identification of Correlated factors for Absenteeism of employees using Clustering techniques.- Chapter 6 Multi-view Data Clustering through Consensus Graph and Data Representation Learning.- Chapter 7 Uber's Contribution to Faster Deep Learning: A Case Study in Distributed Model Training.- Chapter 8 Auto-Weighted Multi-View Clustering with Unified Binary Representation and Deep Initialization.- Chapter 9 Clustering with Adaptive Unsupervised Graph Convolution Network.- Chapter 10 Graph-based Semi-supervised Learning for Multi-view Data Analysis.- Chapter 11 Advancements in Fuzzy Clustering Algorithms for Im-age Processing: A Comprehensive Review and Future Directions.- Chapter 12 Multiview Latent representation learning with feature diversity for clustering.
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Data clustering;Unsupervised learning;Deep learning;Graph Neural Networks;Nongraph data
Chapter 1 Classification of Gougerot-Sjoegren syndrome Based on Artificial Intelligence.- Chapter 2 Deep learning Classification of Venous Thromboembolism based on Ultrasound imaging.- Chapter 3 Synchronization-Driven Community Detection: Dynamic Frequency Tuning Approach.- Chapter 4 Automatic Evolutionary Clustering for Human Activity Discovery.- Chapter 5 Identification of Correlated factors for Absenteeism of employees using Clustering techniques.- Chapter 6 Multi-view Data Clustering through Consensus Graph and Data Representation Learning.- Chapter 7 Uber's Contribution to Faster Deep Learning: A Case Study in Distributed Model Training.- Chapter 8 Auto-Weighted Multi-View Clustering with Unified Binary Representation and Deep Initialization.- Chapter 9 Clustering with Adaptive Unsupervised Graph Convolution Network.- Chapter 10 Graph-based Semi-supervised Learning for Multi-view Data Analysis.- Chapter 11 Advancements in Fuzzy Clustering Algorithms for Im-age Processing: A Comprehensive Review and Future Directions.- Chapter 12 Multiview Latent representation learning with feature diversity for clustering.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
