000 04424nam a22005175i 4500
001 978-0-387-24452-5
003 DE-He213
005 20250710083931.0
007 cr nn 008mamaa
008 100301s2005 xxu| s |||| 0|eng d
020 _a9780387244525
_a99780387244525
024 7 _a10.1007/b105515
_2doi
082 0 4 _a006.6
_223
100 1 _aBhanu, Bir.
_eauthor.
245 1 0 _aEvolutionary Synthesis of Pattern Recognition Systems
_h[recurso electrónico] /
_cby Bir Bhanu, Yingqiang Lin, Krzysztof Krawiec.
264 1 _aNew York, NY :
_bSpringer New York,
_c2005.
300 _aXXIV, 296 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aMonographs in Computer Science,
_x0172-603X
505 0 _aFeature Synthesis for Object Detection -- Mdl-Based Efficient Genetic Programming for Object Detection -- Feature Selection for Object Detection -- Evolutionary Feature Synthesis for Object Recognition -- Linear Genetic Programming for Object Recognition -- Applications of Linear Genetic Programming for Object Recognition -- Summary and Future Work.
520 _aDesigning object detection and recognition systems that work in the real world is a challenging task due to various factors including the high complexity of the systems, the dynamically changing environment of the real world and factors such as occlusion, clutter, articulation, and various noise contributions that make the extraction of reliable features quite difficult. Evolutionary Synthesis of Pattern Recognition Systems presents novel effective approaches based on evolutionary computational techniques, such as genetic programming (GP), linear genetic programming (LGP), coevolutionary genetic programming (CGP) and genetic algorithms (GA) to automate the synthesis and analysis of object detection and recognition systems. The book's concepts, principles, and methodologies will enable readers to automatically build robust and flexible systems-in a systematic manner-that can provide human-competitive performance and reduce the cost of designing and maintaining these systems. Its content covers all key aspects of object recognition: object detection, feature selection, feature discovery, object recognition, domain knowledge. Basic knowledge of programming and data structures, and some calculus, is presupposed. Topics and Features: *Presents integrated coverage of object detection/recognition systems *Describes how new system features can be generated "on the fly," and how systems can be made flexible and applied to a variety of objects and images *Demonstrates how object detection and recognition systems can be automatically designed and maintained in a relatively inexpensive way *Explains automatic synthesis and creation of programs (which saves valuable human and economic resources) *Focuses on results using real-world imagery, thereby concretizing the book's novel ideas This accessible monograph provides the computational foundation for evolutionary synthesis involving pattern recognition and is an ideal overview of the latest concepts and technologies. Computer scientists, researchers, and electrical and computer engineers will find the book a comprehensive resource, and it can serve equally well as a text/reference for advanced students and professional self-study.
650 0 _aCOMPUTER SCIENCE.
650 0 _aARTIFICIAL INTELLIGENCE.
650 0 _aCOMPUTER VISION.
650 0 _aOPTICAL PATTERN RECOGNITION.
650 1 4 _aCOMPUTER SCIENCE.
650 2 4 _aCOMPUTER IMAGING, VISION, PATTERN RECOGNITION AND GRAPHICS.
650 2 4 _aIMAGE PROCESSING AND COMPUTER VISION.
650 2 4 _aPATTERN RECOGNITION.
650 2 4 _aARTIFICIAL INTELLIGENCE (INCL. ROBOTICS).
650 2 4 _aUSER INTERFACES AND HUMAN COMPUTER INTERACTION.
650 2 4 _aCOMPUTATION BY ABSTRACT DEVICES.
700 1 _aLin, Yingqiang.
_eauthor.
700 1 _aKrawiec, Krzysztof.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780387212951
830 0 _aMonographs in Computer Science,
_x0172-603X
856 4 0 _uhttp://dx.doi.org/10.1007/b105515
_zVer el texto completo en las instalaciones del CICY
912 _aZDB-2-SCS
942 _2ddc
_cER
999 _c56348
_d56348