000 03351nam a22005295i 4500
001 978-3-031-55056-0
003 DE-He213
005 20250516160015.0
007 cr nn 008mamaa
008 240323s2024 sz | s |||| 0|eng d
020 _a9783031550560
_9978-3-031-55056-0
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
245 1 0 _aProceedings of ELM 2022
_h[electronic resource] :
_bTheory, Algorithms and Applications /
_cedited by Kaj-Mikael Björk.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aV, 81 p. 32 illus., 31 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aProceedings in Adaptation, Learning and Optimization,
_x2363-6092 ;
_v18
505 0 _aApplication 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.
520 _aThis 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).
541 _fUABC ;
_cPerpetuidad
650 0 _aComputational intelligence.
650 0 _aArtificial intelligence.
650 1 4 _aComputational Intelligence.
650 2 4 _aArtificial Intelligence.
700 1 _aBjörk, Kaj-Mikael.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031550553
776 0 8 _iPrinted edition:
_z9783031550577
776 0 8 _iPrinted edition:
_z9783031550584
830 0 _aProceedings in Adaptation, Learning and Optimization,
_x2363-6092 ;
_v18
856 4 0 _zLibro electrónico
_uhttp://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-3-031-55056-0
912 _aZDB-2-INR
912 _aZDB-2-SXIT
942 _cLIBRO_ELEC
999 _c274601
_d274600