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20200603.0 |
| 008 |
170528s2016 mau eng |
| 020 |
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|a 9780128045367
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| 040 |
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|a UniSZA
|e rda
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| 050 |
0 |
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|a TA1637
|b .B56 2016
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| 090 |
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|a TA1637
|b .B56 2016
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| 245 |
0 |
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|a Bio-inspired computation and applications in image processing
|c Xin-She Yang, Joao Paula Papa
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| 264 |
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1 |
|a Boston, Massachusetts :
|b Elsevier
|c c2016
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| 300 |
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|a xx, 353 pages :
|b illustration ;
|c 25 cm.
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| 336 |
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|a text
|2 rdacontent
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| 337 |
|
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|a unmediated
|2 rdamedia
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| 338 |
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|a volume
|2 rdacarrier
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| 505 |
0 |
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|a 1. Bio-inspired computation and its applications in image processing: an overview -- 2. Fine-tuning enhanced probabilistic neural networks using metaheuristic-driven optimization -- 3. Fine-tuning deep belief networks using cuckoo search -- 4. Improved weighted thresholded histogram equalization algorithm for digital image contrast enhancement using -- 5. Ground-glass opacity nodules detection and segmentation using the snake model -- 7. Mobile object tracking using the modified cuckoo search --7. Toward optimal watermarking of grayscale images using the multiple scaling factor-based cuckoo search technique -- 8. Bat algorithm-based automatic clustering method and its application in image processing -- 9. Multitemporal remote sensing image classification by nature-inspired techniques -- 10. Firefly algorithm for optimized nonrigid demons registration -- 11. Minimizing the mode-change letency in real-time image processing applications -- 12. Learning OWA filters parameters for SAR imagery with multiple polarizations -- 13. Oil reservoir quality assisted by machine learning and evolutionary -- 14. Solving imbalanced dataset problems for high-dimensional image processing by swarm optimization -- 15. Retinal image vasculature analysis software (RIVAS)
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| 520 |
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|a "Bio-Inspired Computation and Applications in Image Processing summarizes the latest developments in bio-inspired computation in image processing, focusing on nature-inspired algorithms that are linked with deep learning, such as ant colony optimization, particle swarm optimization, and bat and firefly algorithms that have recently emerged in the field. In addition to documenting state-of-the-art developments, this book also discusses future research trends in bio-inspired computation, helping researchers establish new research avenues to pursue. Reviews the latest developments in bio-inspired computation in image processing Focuses on the introduction and analysis of the key bio-inspired methods and techniques Combines theory with real-world applications in image processing Helps solve complex problems in image and signal processing Contains a diverse range of self-contained case studies in real-world applications"
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| 650 |
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0 |
|a Image processing
|x Digital techniques
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| 650 |
|
0 |
|a Natural computation
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| 700 |
1 |
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|a Papa, Joao Paula ,
|e editor
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| 700 |
1 |
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|a Yang, Xin-She ,
|e editor
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| 999 |
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|a 1000169390
|b Book
|c OPEN SHELF (30 DAYS)
|e Tembila Campus
|