000 | 03103nam a22005295i 4500 | ||
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001 | 978-3-319-47223-2 | ||
003 | DE-He213 | ||
005 | 20200421111655.0 | ||
007 | cr nn 008mamaa | ||
008 | 161112s2016 gw | s |||| 0|eng d | ||
020 |
_a9783319472232 _9978-3-319-47223-2 |
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024 | 7 |
_a10.1007/978-3-319-47223-2 _2doi |
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050 | 4 | _aQ334-342 | |
050 | 4 | _aTJ210.2-211.495 | |
072 | 7 |
_aUYQ _2bicssc |
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072 | 7 |
_aTJFM1 _2bicssc |
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072 | 7 |
_aCOM004000 _2bisacsh |
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082 | 0 | 4 |
_a006.3 _223 |
245 | 1 | 0 |
_aHybrid Soft Computing for Image Segmentation _h[electronic resource] / _cedited by Siddhartha Bhattacharyya, Paramartha Dutta, Sourav De, Goran Klepac. |
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2016. |
|
300 |
_aXVI, 321 p. 162 illus., 87 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 |
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505 | 0 | _aHybrid Soft Computing Techniques for Image Segmentation: Fundamentals and Applications -- Enhanced Rough-Fuzzy C-Means Algorithm for Image Segmentation -- Intuitionistic Fuzzy C-means Clustering Algorithm for Brain Image Segmentation -- Automatic Segmentation Approaches -- Modified Level Set Segmentation -- Fuzzy Deformable Models for 3D Segmentation of Brain Structures -- Rough Sets for Probabilistic Model Based Image Segmentation -- Segmentation of Cerebral Images. . | |
520 | _aThis book proposes soft computing techniques for segmenting real-life images in applications such as image processing, image mining, video surveillance, and intelligent transportation systems. The book suggests hybrids deriving from three main approaches: fuzzy systems, primarily used for handling real-life problems that involve uncertainty; artificial neural networks, usually applied for machine cognition, learning, and recognition; and evolutionary computation, mainly used for search, exploration, efficient exploitation of contextual information, and optimization. The contributed chapters discuss both the strengths and the weaknesses of the approaches, and the book will be valuable for researchers and graduate students in the domains of image processing and computational intelligence. | ||
650 | 0 | _aComputer science. | |
650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aComputer graphics. | |
650 | 0 | _aComputational intelligence. | |
650 | 1 | 4 | _aComputer Science. |
650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
650 | 2 | 4 | _aComputational Intelligence. |
650 | 2 | 4 | _aComputer Imaging, Vision, Pattern Recognition and Graphics. |
700 | 1 |
_aBhattacharyya, Siddhartha. _eeditor. |
|
700 | 1 |
_aDutta, Paramartha. _eeditor. |
|
700 | 1 |
_aDe, Sourav. _eeditor. |
|
700 | 1 |
_aKlepac, Goran. _eeditor. |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783319472225 |
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-319-47223-2 |
912 | _aZDB-2-SCS | ||
942 | _cEBK | ||
999 |
_c54631 _d54631 |