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  1. 1
    An elementary introduction to statistical learning theory / Sanjeev Kulkarni, Gilbert Harman.

    An elementary introduction to statistical learning theory / Sanjeev Kulkarni, Gilbert Harman. by Kulkarni, Sanjeev

    Published 2011
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  2. 2
    The Bioinformatics : Machine Learning Approach.

    The Bioinformatics : Machine Learning Approach. by Brunak, Søren

    Published 2001
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  3. 3
    3D Shape Analysis : Fundamentals, Theory and Applications.

    3D Shape Analysis : Fundamentals, Theory and Applications. by Tabia, Hedi

    Published 2018
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  4. 4
    Bridging the gap between graph edit distance and kernel machines / Michel Neuhaus, Horst Bunke.

    Bridging the gap between graph edit distance and kernel machines / Michel Neuhaus, Horst Bunke. by Neuhaus, Michel

    Published 2007
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  5. 5
    Machine interpretation of patterns : image analysis and data mining / editors, Rajat K. De, Deba Prasad Mandal, Ashish Ghosh.

    Machine interpretation of patterns : image analysis and data mining / editors, Rajat K. De, Deba Prasad Mandal, Ashish Ghosh.

    Published 2010
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  6. 6
    Advanced methods and deep learning in computer vision / edited by E.R. Davies, Matthew A. Turk.

    Advanced methods and deep learning in computer vision / edited by E.R. Davies, Matthew A. Turk.

    Published 2022
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  7. 7
    Anomaly Detection in Video Surveillance by Xiaochun Wang.

    Anomaly Detection in Video Surveillance by Xiaochun Wang. by Wang, Xiaochun

    Published 2024
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  8. 8
    Fundamentals of Pattern Recognition and Machine Learning by Ulisses Braga-Neto.

    Fundamentals of Pattern Recognition and Machine Learning by Ulisses Braga-Neto. by Braga-Neto, Ulisses

    Published 2024
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  9. 9
    Document Analysis Systems 16th IAPR International Workshop, DAS 2024, Athens, Greece, August 30–31, 2024, Proceedings / edited by Giorgos Sfikas, George Retsinas.

    Document Analysis Systems 16th IAPR International Workshop, DAS 2024, Athens, Greece, August 30–31, 2024, Proceedings / edited by Giorgos Sfikas, George Retsinas.

    Published 2024
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  10. 10
    Time series with PyTorch : modern deep learning toolkit for real-world forecasting challenges / Graeme Davidson, Lei Ma.

    Time series with PyTorch : modern deep learning toolkit for real-world forecasting challenges / Graeme Davidson, Lei Ma. by Davidson, Graeme, Ma, Lei

    Published 2024
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  11. 11
    An elementary introduction to statistical learning theory / Sanjeev Kulkarni, Gilbert Harman.

    An elementary introduction to statistical learning theory / Sanjeev Kulkarni, Gilbert Harman. by Kulkarni, Sanjeev

    Published 2011
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  12. 12
    Pattern recognition and machine learning / Christopher M. Bishop.

    Pattern recognition and machine learning / Christopher M. Bishop. by Bishop, Christopher M.

    Published 2006
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  13. 13
    Introduction to pattern recognition and machine learning / M Narasimha Murty, Der V Susheela Devi (Indian Institute of Science, India).

    Introduction to pattern recognition and machine learning / M Narasimha Murty, Der V Susheela Devi (Indian Institute of Science, India). by Murty, M. Narasimha, Devi, V. Susheela

    Published 2015
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  14. 14
    3D Shape Analysis : Fundamentals, Theory and Applications.

    3D Shape Analysis : Fundamentals, Theory and Applications. by Tabia, Hedi

    Published 2018
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  15. 15
    Computing in Civil Engineering 2019 : Data, sensing, and analytics : selected papers from the ASCE International Conference on Computing in Civil Engineering 2019, June 17-19, 2019, Atlanta, Georgia / sponsored by Computing Division of the American Society of Civil Engineers ; edited by Yong K. Cho, Fernanda Leite, Amir Behzadan, Chao Wang.

    Computing in Civil Engineering 2019 : Data, sensing, and analytics : selected papers from the ASCE International Conference on Computing in Civil Engineering 2019, June 17-19, 2019...

    Published 2019
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  16. 16
    Pattern Recognition 43rd DAGM German Conference, DAGM GCPR 2021, Bonn, Germany, September 28 – October 1, 2021, Proceedings / edited by Christian Bauckhage, Juergen Gall, Alexander Schwing.

    Pattern Recognition 43rd DAGM German Conference, DAGM GCPR 2021, Bonn, Germany, September 28 – October 1, 2021, Proceedings / edited by Christian Bauckhage, Juergen Gall, Alexander...

    Published 2021
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  17. 17
    Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications 25th Iberoamerican Congress, CIARP 2021, Porto, Portugal, May 10–13, 2021, Revised Selected Papers / edited by João Manuel R. S. Tavares, João Paulo Papa, Manuel González Hidalgo.

    Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications 25th Iberoamerican Congress, CIARP 2021, Porto, Portugal, May 10–13, 2021, Revised Selected Paper...

    Published 2021
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  18. 18
    COMPUTER VISION PROJECTS WITH PYTORCH design and develop production-grade models / Akshay Kulkarni, Adarsha Shivananda, Nitin Ranjan Sharma.

    COMPUTER VISION PROJECTS WITH PYTORCH design and develop production-grade models / Akshay Kulkarni, Adarsha Shivananda, Nitin Ranjan Sharma. by Kulkarni, Akshay

    Published 2022
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  19. 19
    Handbook of Fingerprint Recognition by Davide Maltoni, Dario Maio, Anil K. Jain, Jianjiang Feng.

    Handbook of Fingerprint Recognition by Davide Maltoni, Dario Maio, Anil K. Jain, Jianjiang Feng. by Maltoni, Davide, Maio, Dario, Jain, Anil K., Feng, Jianjiang

    Published 2022
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  20. 20
    Image Analysis and Processing – ICIAP 2022 21st International Conference, Lecce, Italy, May 23–27, 2022, Proceedings, Part I / edited by Stan Sclaroff, Cosimo Distante, Marco Leo, Giovanni M. Farinella, Federico Tombari.

    Image Analysis and Processing – ICIAP 2022 21st International Conference, Lecce, Italy, May 23–27, 2022, Proceedings, Part I / edited by Stan Sclaroff, Cosimo Distante, Marco Leo,...

    Published 2022
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