03316nam a22005175i 4500 978-3-031-55056-0 DE-He213 20251030111741.0 cr nn 008mamaa 240323s2024 sz | s |||| 0|eng d 9783031550560 978-3-031-55056-0 10.1007/978-3-031-55056-0 doi Q342 UYQ bicssc COM004000 bisacsh UYQ thema Proceedings of ELM 2022 [electronic resource] : Theory, Algorithms and Applications / edited by Kaj-Mikael Björk. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. V, 81 p. 32 illus., 31 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Proceedings in Adaptation, Learning and Optimization, 2363-6092 ; 18 Application of ELM model to the motion detection of vehicles under moving background -- Distributed memory-efficient algorithm for Extreme Learning Machines based on Spark -- Does streaming affect video game popularity? -- Massive Offline Signature Forgery Detection with Extreme Learning Machines -- Importance of the Activation Function in Extreme Learning Machine for Acid Sulfate Soil Classification. This book contains selected papers from the 12th International Conference on Extreme Learning Machines 2022. Extreme learning machines (ELMs) continue to be an important complement to the many deep learning models you can find in the machine learning domain. ELM is fast and therefore suitable for many applications (not only in edge computing), and therefore there is a need to gather examples of possible applications. These proceedings, for the ELM 2022 conference, cover several application areas with relevant topics, where ELM can be used and has been used with great success. Here you will find several new areas (gaming, for instance) as well as improved concepts for existing application areas (signature forgery, for instance), where ELM has been implemented. In addition, some method improvements are also covered in this book, more specifically on the topic of 2nd-order Ordinary Differential Equations (ODEs). Computational intelligence. 64052 Artificial intelligence. 58441 Computational Intelligence. 64052 Artificial Intelligence. 58441 Björk, Kaj-Mikael. editor. edt http://id.loc.gov/vocabulary/relators/edt 73831 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031550553 Printed edition: 9783031550577 Printed edition: 9783031550584 Proceedings in Adaptation, Learning and Optimization, 2363-6092 ; 18 73832 https://doi.org/10.1007/978-3-031-55056-0 ZDB-2-INR ZDB-2-SXIT 58606 58606