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|a 9781681730127
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|a 10.2200/S00819ED1V01Y201712COV014
|2 doi
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|b D253 2018
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|a 006.4
|2 23
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| 100 |
1 |
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|a Dana, Kristin J.,
|d 1968-
|e author.
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| 245 |
1 |
0 |
|a Computational texture and patterns :
|b from textons to deep learning /
|c Kristin J. Dana.
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| 264 |
|
1 |
|a [San Rafael, California] :
|b Morgan & Claypool,
|c 2018.
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| 300 |
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|a 1 online resource (xiii, 99 pages) :
|b illustrations.
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| 336 |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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| 490 |
1 |
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|a Synthesis lectures on computer vision,
|x 2153-1064 ;
|v # 14
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| 504 |
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|a Includes bibliographical references (pages 77-98).
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| 505 |
0 |
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|a 1. Visual patterns and texture -- 1.1 Patterns in nature -- 1.2 Big data patterns -- 1.3 Temporal patterns -- 1.4 Organization --
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| 505 |
8 |
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|a 2. Textons in human and computer vision -- 2.1 Pre-attentive vision -- 2.2 Texton: the early definition -- 2.3 What are textons? Then and now --
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| 505 |
8 |
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|a 3. Texture recognition -- 3.1 Traditional methods of texture recognition -- 3.2 From textons to deep learning for recognition -- 3.3 Texture recognition with deep learning -- 3.4 Material recognition vs. texture recognition --
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| 505 |
8 |
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|a 4. Texture segmentation -- 4.1 Traditional methods of texture segmentation -- 4.1.1 Graph-based methods -- 4.1.2 Mean shift methods -- 4.1.3 Markov random fields -- 4.2 Segmentation with deep learning --
|
| 505 |
8 |
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|a 5. Texture synthesis -- 5.1 Traditional methods for texture synthesis -- 5.2 Texture synthesis with deep learning --
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| 505 |
8 |
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|a 6. Texture style transfer -- 6.1 Traditional methods of style transfer -- 6.2 Texture style transfer with deep learning -- 6.3 Face style transfer --
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| 505 |
8 |
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|a 7. Return of the pyramids -- 7.1 Advantages of pyramid methods --
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| 505 |
8 |
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|a 8. Open issues in understanding visual patterns -- 8.1 Discovering unknown patterns -- 8.2 Detecting subtle change -- 8.3 Perceptual metrics --
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| 505 |
8 |
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|a 9. Applications for texture and patterns -- 9.1 Medical imaging and quantitative dermatology -- 9.2 Texture matching in industry -- 9.3 E-commerce -- 9.4 Textured solar panels -- 9.5 Road analysis for automated driving --
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| 505 |
8 |
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|a 10. Tools for mining patterns: cloud services and software libraries -- 10.1 Software libraries -- 10.2 Cloud services --
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| 505 |
8 |
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|a A. A concise description of deep learning -- A.1 Multilayer perceptron -- A.2 Convolutional neural networks -- A.3 Alexnet, Dense-Net, Res-Nets, and all that --
|
| 505 |
8 |
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|a Bibliography -- Author's biography.
|
| 533 |
|
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|a Electronic reproduction.
|b Ann Arbor, MI
|n Available via World Wide Web.
|
| 588 |
|
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|a Title from PDF title page (viewed on September 26, 2018).
|
| 650 |
|
0 |
|a Pattern recognition systems.
|
| 650 |
|
0 |
|a Texture mapping.
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| 653 |
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|a texture
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| 653 |
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|a patterns
|
| 653 |
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|a deep learning
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| 653 |
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|a machine learning
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| 653 |
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|a segmentation
|
| 653 |
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|a synthesis
|
| 653 |
|
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|a recognition
|
| 653 |
|
|
|a textons
|
| 653 |
|
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|a style transfer
|
| 710 |
2 |
|
|a ProQuest (Firm)
|
| 776 |
0 |
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|i Print version:
|z 9781681730110
|z 9781681732695
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| 830 |
|
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|a Synthesis lectures on computer vision ;
|v # 14.
|x 2153-1064
|
| 856 |
4 |
0 |
|u https://ebookcentral.proquest.com/lib/santaclara/detail.action?docID=5520203
|z Connect to this title online (unlimited simultaneous users allowed; 325 uses per year)
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