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1

Siddiqui, Fasahat Ullah, e Abid Yahya. Clustering Techniques for Image Segmentation. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-81230-0.

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2

Roland, Wilson. Image segmentation and uncertainty. Letchworth, Herts., England: Research Studies Press, 1988.

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3

Ismail, Ben Ayed, a cura di. Variational and level set methods in image segmentation. Berlin: Springer Verlag, 2010.

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4

Leppäjärvi, Seppo. Image segmentation and analysis for automatic color correction. Lappeenranta, Finland: Lappeenranta University of Technology, 1999.

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5

Gorte, Ben. Probabilistic segmentation of remotely sensed images. Enschede: International Institute for Aerospace Survey and Earth Sciences (ITC), 1998.

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6

Vernon, David. Fourier vision: Segmentation and velocity measurement using the Fourier transform. Boston: Kluwer Academic, 2001.

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7

Nitzberg, M. Filtering, segmentation, and depth. Berlin: Springer-Verlag, 1993.

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8

Video segmentation and its applications. New York: Springer, 2011.

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9

Batra, Dhruv. Interactive Co-segmentation of Objects in Image Collections. New York, NY: Springer Science+Business Media, LLC, 2011.

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10

1956-, Solimini Sergio, a cura di. Variational methods in image segmentation: With seven image processing experiments. Boston: Birkhäuser, 1995.

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11

Abkar, Ali Akbar. Likelihood-based segmentation and classification of remotely sensed images: A Bayesian optimization approach for combining RS and GIS. Enschede, The Netherlands: International Institute for Aerospace Survey and Earth Sciences, 1999.

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12

El-Baz, Ayman S. Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies: Volume 1. Boston, MA: Springer Science+Business Media, LLC, 2011.

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13

Digital image processing. 6a ed. Berlin: Springer, 2005.

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14

Computational analysis of visual motion. New York: Plenum Press, 1994.

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15

Jähne, Bernd. Digital image processing: Concepts, algorithms, and scientific applications. 2a ed. Berlin: Springer-Verlag, 1993.

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16

Digital image processing: Concepts, algorithms, and scientific applications. 4a ed. Berlin: Springer, 1997.

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17

Jähne, Bernd. Digital image processing: Concepts, algorithms, and scientific applications. 3a ed. Berlin: Springer-Verlag, 1995.

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18

Jähne, Bernd. Digital image processing: Concepts, algorithms, and scientific applications. Berlin: Springer-Verlag, 1991.

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19

Yahya, Abid, e Fasahat Ullah Siddiqui. Clustering Techniques for Image Segmentation. Springer International Publishing AG, 2021.

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20

Yahya, Abid, e Fasahat Ullah Siddiqui. Clustering Techniques for Image Segmentation. Springer International Publishing AG, 2022.

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21

A summary of image segmentation techniques. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1993.

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22

Lei, Tao, e Asoke K. Nandi. Image Segmentation: Principles, Techniques, and Applications. Wiley & Sons, Incorporated, John, 2022.

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23

Lei, Tao, e Asoke K. Nandi. Image Segmentation: Principles, Techniques, and Applications. Wiley & Sons, Incorporated, John, 2022.

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24

Lei, Tao, e Asoke K. Nandi. Image Segmentation: Principles, Techniques, and Applications. Wiley & Sons, Limited, John, 2022.

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25

Lei, Tao, e Asoke K. Nandi. Image Segmentation: Principles, Techniques, and Applications. Wiley & Sons, Incorporated, John, 2022.

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26

Advances in Image And Video Segmentation. IRM Press, 2006.

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27

Acton, Scott, e Nilanjan Ray. Biomedical Image Analysis: Segmentation. Springer International Publishing AG, 2009.

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28

Acton, Scott, e Nilanjan Ray. Biomedical Image Analysis: Segmentation. Morgan & Claypool Publishers, 2009.

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29

Rezaee, M. Ramze. Application of fuzzy techniques in image segmentation. University of Leiden], 1998.

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30

Advances in Image and Video Segmentation. Irm Press, 2006.

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31

Image Segmentation and Compression Using Hidden Markov Models. Springer, 2000.

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32

Jean Michel Morel Sergio Solimini. Variational Methods in Image Segmentation: With seven image processing experiments. Birkhäuser Boston, 2012.

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33

Ayed, Ismail Ben. High-Order Models in Semantic Image Segmentation. Elsevier Science & Technology Books, 2021.

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34

High-Order Models in Semantic Image Segmentation. Elsevier Science & Technology, 2029.

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35

Mitiche, Amar, e Ismail Ben Ayed. Variational and Level Set Methods in Image Segmentation. Springer, 2010.

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36

Mitiche, Amar, e Ismail Ben Ayed. Variational and Level Set Methods in Image Segmentation. Springer, 2011.

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37

Mitiche, Amar, e Ismail Ben Ayed. Variational and Level Set Methods in Image Segmentation. Springer, 2012.

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38

Kuo, C. C. Jay, Jia He e Chang-Su Kim. Interactive Segmentation Techniques: Algorithms and Performance Evaluation. Springer London, Limited, 2013.

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39

Kuo, C. C. Jay, Jia He e Chang-Su Kim. Interactive Segmentation Techniques: Algorithms and Performance Evaluation. Springer, 2013.

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40

Brain Tumor MRI Image Segmentation Using Deep Learning Techniques. Elsevier, 2022. http://dx.doi.org/10.1016/c2021-0-00056-0.

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41

Chaki, Jyotismita. Brain Tumor MRI Image Segmentation Using Deep Learning Techniques. Elsevier Science & Technology, 2021.

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42

Chaki, Jyotismita. Brain Tumor MRI Image Segmentation Using Deep Learning Techniques. Elsevier Science & Technology Books, 2021.

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43

Acton, Scott T., e Nilanjan Ray. Biomedical Image Analysis: Segmentation (Synthesis Lectures on Image, Video, & Multimedia Processing). Morgan & Claypool Publishers, 2007.

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44

Ngan, King Ngi, e Hongliang Li. Video Segmentation and Its Applications. Springer, 2014.

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45

Ngan, King Ngi, e Hongliang Li. Video Segmentation and Its Applications. Springer, 2011.

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46

Batra, Dhruv, Adarsh Kowdle e Devi Parikh. Interactive Co-segmentation of Objects in Image Collections. Springer, 2011.

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47

GOYAL, Sudha, e Neeti TANEJA. Enhancing the Operating Efficiency of Membrane Filter Using Image Segmentation Techniques. Independently Published, 2018.

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48

Solimini, Sergio, e Jean-Michel Morel. Variational Methods in Image Segmentation: With Seven Image Processing Experiments. Birkhauser Verlag, 2012.

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49

Sun, Changming, Hugues Talbot, Sebastien Ourselin e Tony Adriaansen, a cura di. Digital Image Computing: Techniques and Applications. CSIRO Publishing, 2003. http://dx.doi.org/10.1071/9780643090989.

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Abstract (sommario):
Digital Image Computing: Techniques and Applications is the premier biennial conference in Australia on the topics of image processing and image analysis. This seventh edition of the proceedings has seen an unprecedented level of submission, on such diverse areas as: Image processing; Face recognition; Segmentation; Registration; Motion analysis; Medical imaging; Object recognition; Virtual environments; Graphics; Stereo-vision; and Video analysis. These two volumes contain all the 108 accepted papers and five invited talks that were presented at the conference. These two volumes provide the Australian and international imaging research community with a snapshot of current theoretical and practical developments in these areas. They are of value to any engineer, computer scientist, mathematician, statistician or student interested in these matters.
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50

Insight into Images: Principles and Practice for Segmentation, Registration, and Image Analysis. AK Peters, 2004.

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