Jun Shen - Böcker
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5 produkter
5 produkter
- Nyhet
Del 16041 - Lecture Notes in Computer Science
Big Data and Artificial Intelligence
13th International Conference, BDA 2025, Bangalore, India, July 17–20, 2025, Proceedings
Häftad, Engelska, 2026
796 kr
Skickas inom 10-15 vardagar
This book constitutes the proceedings of the 13th International Conference on Big Data and Artificial Intelligence, BDA 2025, held in Bangalore, India, during July 17–20, 2025.The 15 full papers and 13 short papers included in this book were carefully reviewed and selected from 104 submissions. They were organized in topical sections as follows: Language Understanding and Interactive AI; Learning Paradigms and Optimisations; ML Frameworks and System-Level Intelligence; Deep Learning Architectures and Model Design; Deep Learning Architecture and Adaptations; Domain-Specific AI Models; and Fine-Tuning and Generative Modeling Techniques.
Del 44 - Series In Machine Perception And Artificial Intelligence
Multispectral Image Processing And Pattern Recognition
Inbunden, Engelska, 2001
1 417 kr
Tillfälligt slut
A study of multispectral image processing and pattern recognition. It covers: geometric and orthogonal moments; minimum description length method for facet matching; an integrated vision system for ALV navigation; fuzzy Bayesian networks; and more.
1 073 kr
Skickas inom 10-15 vardagar
This thesis develops several systematic and unified approaches for analyzing dynamic systems with positive characteristics or a more general cone invariance property. Based on these analysis results, it uses linear programming tools to address static output feedback synthesis problems with a focus on optimal gain performances. Owing to their low computational complexity, the established controller design algorithms are applicable for large-scale systems. The theory and control strategies developed will not only be useful in handling large-scale positive delay systems with improved solvability and at lower cost, but also further our understanding of the system characteristics in other related areas, such as distributed coordination of networked multi-agent systems, formation control of multiple robots.
1 073 kr
Skickas inom 10-15 vardagar
This thesis develops several systematic and unified approaches for analyzing dynamic systems with positive characteristics or a more general cone invariance property. Based on these analysis results, it uses linear programming tools to address static output feedback synthesis problems with a focus on optimal gain performances. Owing to their low computational complexity, the established controller design algorithms are applicable for large-scale systems. The theory and control strategies developed will not only be useful in handling large-scale positive delay systems with improved solvability and at lower cost, but also further our understanding of the system characteristics in other related areas, such as distributed coordination of networked multi-agent systems, formation control of multiple robots.
Del 5 - Intelligent Information Systems
Adaptive Micro Learning - Using Fragmented Time To Learn
Inbunden, Engelska, 2020
1 132 kr
Skickas inom 5-8 vardagar
This compendium introduces an artificial intelligence-supported solution to realize adaptive micro learning over open education resource (OER). The advantages of cloud computing and big data are leveraged to promote the categorization and customization of OERs micro learning context. For a micro-learning service, OERs are tailored into fragmented pieces to be consumed within shorter time frames.Firstly, the current status of mobile-learning, micro-learning, and OERs are described. Then, the significances and challenges of Micro Learning as a Service (MLaaS) are discussed. A framework of a service-oriented system is provided, which adopts both online and offline computation domain to work in conjunction to improve the performance of learning resource adaptation.In addition, a comprehensive learner model and a knowledge base is prepared to semantically profile the learners and learning resource. The novel delivery and access mode of OERs suffers from the cold start problem because of the shortage of already-known learner information versus the continuously released new micro OERs. This unique volume provides an excellent feasible algorithmic solution to overcome the cold start problem.