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Books on the topic 'Machine processing'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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1

Klyepikov, Viktor. Processing equipment. Machine accessories. ru: INFRA-M Academic Publishing LLC., 2017. http://dx.doi.org/10.12737/24563.

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2

Machine transcription for document processing. 3rd ed. Cincinnati, Ohio: South-Western Educational Pub., 1995.

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3

Swain, Debabala, Prasant Kumar Pattnaik, and Pradeep K. Gupta, eds. Machine Learning and Information Processing. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1884-3.

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4

Agarwal, Sonali, Shekhar Verma, and Dharma P. Agrawal, eds. Machine Intelligence and Signal Processing. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1366-4.

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5

Singh, Richa, Mayank Vatsa, Angshul Majumdar, and Ajay Kumar, eds. Machine Intelligence and Signal Processing. New Delhi: Springer India, 2016. http://dx.doi.org/10.1007/978-81-322-2625-3.

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6

Swain, Debabala, Prasant Kumar Pattnaik, and Tushar Athawale, eds. Machine Learning and Information Processing. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4859-2.

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7

Vaclav, Hlavac, and Boyle Roger, eds. Image processing, analysis, and machine vision. 2nd ed. Pacific Grove, CA: PWS Pub., 1999.

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8

Sonka, Milan. Image processing, analysis, and machine vision. London: Chapman & Hall Computing, 1993.

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9

Batchelor, Bruce G. Interactive Image Processing for Machine Vision. London: Springer London, 1993.

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10

Mueller, Cheryl. Circles, Ltd.: Word processing machine transcription. Englewood Cliffs, NJ: Prentice-Hall, 1987.

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11

Roger, Boyle, and Hlavac Vaclav, eds. Image processing, analysis, and machine vision. 3rd ed. Toronto [u.a.]: Thomson, 2008.

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12

Akansu, Ali N., Sanjeev R. Kulkarni, and Dmitry Malioutov, eds. Financial Signal Processing and Machine Learning. Chichester, UK: John Wiley & Sons, Ltd, 2016. http://dx.doi.org/10.1002/9781118745540.

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13

Singh, Himanshu. Practical Machine Learning and Image Processing. Berkeley, CA: Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-4149-3.

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14

Sonka, Milan, Vaclav Hlavac, and Roger Boyle. Image Processing, Analysis and Machine Vision. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4899-3216-7.

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15

Batchelor, Bruce G., and Frederick Waltz. Interactive Image Processing for Machine Vision. London: Springer London, 1993. http://dx.doi.org/10.1007/978-1-4471-0393-6.

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16

Vaclav, Hlavac, and Boyle Roger 1954-, eds. Image processing, analysis, and machine vision. 3rd ed. Toronto: Thompson Learning, 2008.

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17

Batchelor, Bruce G. Interactive image processing for machine vision. London: Springer-Verlag, 1993.

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18

Galbiati, Louis J. Machine vision and digital image processing fundamentals. Englewood Cliffs, N.J: Prentice Hall, 1990.

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19

Ettinger, Blanche. Machine transcription: Language skills for information processing. 2nd ed. Eden Prairie, MN: Paradigm, 1992.

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20

Galbiati, Louis J. Machine vision and digital image processing fundamentals. Englewood Cliffs, N.J: Prentice-Hall, 1990.

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21

Pathak, Manas A. Privacy-Preserving Machine Learning for Speech Processing. New York, NY: Springer New York, 2013.

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22

Pathak, Manas A. Privacy-Preserving Machine Learning for Speech Processing. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-4639-2.

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23

Soh, Ping Jack, Wai Lok Woo, Hamzah Asyrani Sulaiman, Mohd Azlishah Othman, and Mohd Shakir Saat, eds. Advances in Machine Learning and Signal Processing. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32213-1.

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24

Wilks, Yorick. Machine Conversations. Boston, MA: Springer US, 1999.

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25

Machine vision: theory, algorithms, practicalities. London: Academic, 1990.

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26

Vision in man and machine. New York: McGraw-Hill, 1985.

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27

Image acquisition and pre-processing for machine vision. Bellingham, Wash: SPIE, 2010.

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28

Agrawal, S. S., Amita Devi, Ritika Wason, and Poonam Bansal, eds. Speech and Language Processing for Human-Machine Communications. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-6626-9.

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29

Olive, Joseph, Caitlin Christianson, and John McCary, eds. Handbook of Natural Language Processing and Machine Translation. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-7713-7.

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30

Myles, White John, ed. Machine learning for hackers. Sebastopol, CA: O'Reilly Media, 2012.

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31

W, Cannon James, ed. Word processing in groups. Boston: Jones and Bartlett Publishers, 1992.

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32

Computer aided machine design. New York: Prentice Hall, 1988.

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33

Computer integrated machine design. Upper Saddle River, N.J: Prentice Hall, 1997.

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34

E, Wilson Charles. Computer integrated machine design. Upper Saddle River, NJ: Prentice-Hall International, 1997.

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35

Speech communications: Human and machine. 2nd ed. New York: Institute of Electrical and Electronics Engineers, 1999.

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36

Machine translation. Boca Raton: Taylor & Francis, A CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Franck, Chapman and Hall/CRC, 2015.

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37

Beame, Paul W. Lower bounds in parallel machine computation. Toronto, Ont: University of Toronto, Dept. of Computer Science, 1986.

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38

Pugh, Nelda Spain. Machine transcription: A simulation. Englewood, Cliffs, N.J: Prentice Hall, 1989.

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39

Mitkov, Ruslan. Anaphora resolution in natural language processing and machine translation. Saarbrücken: Institut der Gesellschaft zur Förderung der Angewandten Informationsforschung, 1995.

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40

Machine Transcription Word Processing. Thomson South-Western, 1999.

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41

Pasewark, William R. Machine Transcription for Document Processing :. 3rd ed. International Thomson Publishing, 1994.

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42

Bingham, Philip, and Kurt S. Niel. Image Processing - Machine Vision Applications. SPIE, 2014.

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43

Pasewark, William R. Machine Transcription for Document Processing :. 3rd ed. International Thomson Publishing, 1994.

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44

Pasewark, William R. Machine Transcription for Document Processing :. 3rd ed. International Thomson Publishing, 1994.

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45

Little, Max A. Machine Learning for Signal Processing. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198714934.001.0001.

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Abstract:

Digital signal processing (DSP) is one of the ‘foundational’ engineering topics of the modern world, without which technologies such the mobile phone, television, CD and MP3 players, WiFi and radar, would not be possible. A relative newcomer by comparison, statistical machine learning is the theoretical backbone of exciting technologies such as automatic techniques for car registration plate recognition, speech recognition, stock market prediction, defect detection on assembly lines, robot guidance and autonomous car navigation. Statistical machine learning exploits the analogy between intelligent information processing in biological brains and sophisticated statistical modelling and inference. DSP and statistical machine learning are of such wide importance to the knowledge economy that both have undergone rapid changes and seen radical improvements in scope and applicability. Both make use of key topics in applied mathematics such as probability and statistics, algebra, calculus, graphs and networks. Intimate formal links between the two subjects exist and because of this many overlaps exist between the two subjects that can be exploited to produce new DSP tools of surprising utility, highly suited to the contemporary world of pervasive digital sensors and high-powered and yet cheap, computing hardware. This book gives a solid mathematical foundation to, and details the key concepts and algorithms in, this important topic.

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46

Blanding, Douglass L. Exact Constraint: Machine Design Using Kinematic Processing. American Society of Mechanical Engineers, 1999.

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47

Signal Processing and Machine Learning for Brain-Machine Interfaces. The Institution of Engineering and Technology, 2018.

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48

Tanaka, Toshihisa, and Mahnaz Arvaneh, eds. Signal Processing and Machine Learning for Brain-Machine Interfaces. Institution of Engineering and Technology, 2018. http://dx.doi.org/10.1049/pbce114e.

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49

Akansu, Ali N., Sanjeev R. Kulkarni, and Dmitry M. Malioutov. Financial Signal Processing and Machine Learning. Wiley & Sons, Incorporated, John, 2016.

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50

Boyle, Roger, Milan Sonka, and Vaclav Hlavac. Image Processing: Analysis and Machine Vision. 2nd ed. Thomson-Engineering, 1998.

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