000 | 04292nam a22005655i 4500 | ||
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001 | 978-3-031-16868-0 | ||
003 | DE-He213 | ||
005 | 20240207153501.0 | ||
007 | cr nn 008mamaa | ||
008 | 221108s2023 sz | s |||| 0|eng d | ||
020 |
_a9783031168680 _9978-3-031-16868-0 |
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_a006.3 _223 |
100 | 1 |
_aSun, Yanan. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
245 | 1 | 0 |
_aEvolutionary Deep Neural Architecture Search: Fundamentals, Methods, and Recent Advances _h[electronic resource] / _cby Yanan Sun, Gary G. Yen, Mengjie Zhang. |
250 | _a1st ed. 2023. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2023. |
|
300 |
_aXVI, 331 p. 91 illus., 77 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aStudies in Computational Intelligence, _x1860-9503 ; _v1070 |
|
500 | _aAcceso multiusuario | ||
505 | 0 | _aPart I: Fundamentals and Backgrounds -- Evolutionary Computation -- Deep Neural Networks -- Part II: Evolutionary Deep Neural Architecture Search for Unsupervised DNNs -- Architecture Design for Stacked AEs and DBNs -- Architecture Design for Convolutional Auto-Encoders -- Architecture Design for Variational Auto-Encoders -- Part III: Evolutionary Deep Neural Architecture Search for Supervised DNNs -- Architecture Design for Plain CNNs -- Architecture Design for RBs and DBs Based CNNs -- Architecture Design for Skip-Connection Based CNNs -- Hybrid GA and PSO for Architecture Design -- Internet Protocol Based Architecture Design -- Differential Evolution for Architecture Design -- Architecture Design for Analyzing Hyperspectral Images -- Part IV: Recent Advances in Evolutionary Deep Neural Architecture Search -- Encoding Space Based on Directed Acyclic Graphs -- End-to-End Performance Predictors -- Deep Neural Architecture Pruning -- Deep Neural Architecture Compression -- Distribution Training Framework for Architecture Design. | |
520 | _aThis book systematically narrates the fundamentals, methods, and recent advances of evolutionary deep neural architecture search chapter by chapter. This will provide the target readers with sufficient details learning from scratch. In particular, the method parts are devoted to the architecture search of unsupervised and supervised deep neural networks. The people, who would like to use deep neural networks but have no/limited expertise in manually designing the optimal deep architectures, will be the main audience. This may include the researchers who focus on developing novel evolutionary deep architecture search methods for general tasks, the students who would like to study the knowledge related to evolutionary deep neural architecture search and perform related research in the future, and the practitioners from the fields of computer vision, natural language processing, and others where the deep neural networks have been successfully and largely used in their respective fields. | ||
541 |
_fUABC ; _cPerpetuidad |
||
650 | 0 | _aComputational intelligence. | |
650 | 0 | _aArtificial intelligence. | |
650 | 1 | 4 | _aComputational Intelligence. |
650 | 2 | 4 | _aArtificial Intelligence. |
700 | 1 |
_aYen, Gary G. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
700 | 1 |
_aZhang, Mengjie. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031168673 |
776 | 0 | 8 |
_iPrinted edition: _z9783031168697 |
776 | 0 | 8 |
_iPrinted edition: _z9783031168703 |
830 | 0 |
_aStudies in Computational Intelligence, _x1860-9503 ; _v1070 |
|
856 | 4 | 0 |
_zLibro electrónico _uhttp://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-3-031-16868-0 |
912 | _aZDB-2-INR | ||
912 | _aZDB-2-SXIT | ||
942 | _cLIBRO_ELEC | ||
999 |
_c260633 _d260632 |