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Books on the topic 'Feature Extraction and Classification'

Author: Grafiati

Published: 9 September 2021

Last updated: 1 February 2022

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1

Lee, Chulhee. Feature extraction and classification algorithms for high dimensional data. West Lafayette, Ind: School of Electrical Engineering, Purdue University, 1993.

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2

Eyben, Florian. Real-time Speech and Music Classification by Large Audio Feature Space Extraction. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27299-3.

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3

Guyon, Isabelle, Masoud Nikravesh, Steve Gunn, and Lotfi A. Zadeh, eds. Feature Extraction. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/978-3-540-35488-8.

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4

Chaki, Jyotismita, and Nilanjan Dey. Image Color Feature Extraction Techniques. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-5761-3.

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5

Liu, Huan, and Hiroshi Motoda, eds. Feature Extraction, Construction and Selection. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5725-8.

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6

S, Aguado Alberto, ed. Feature extraction and image processing. Oxford: Newnes, 2002.

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7

Rand, Robert S. Texture analysis and cartographic feature extraction. Fort Belvoir, Va: U.S. Army Corps of Engineers, Engineer Topographic Laboratories, 1985.

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8

Hu, Li, and Zhiguo Zhang, eds. EEG Signal Processing and Feature Extraction. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9113-2.

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9

Agarwal, Basant, and Namita Mittal. Prominent Feature Extraction for Sentiment Analysis. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-25343-5.

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10

Taguchi, Y.-h. Unsupervised Feature Extraction Applied to Bioinformatics. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-22456-1.

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11

Hornik, K. Convergence analysis of local feature extraction algorithms. [Urbana, Ill.]: College of Commerce and Business Administration, University of Illinois at Urbana-Champaign, 1990.

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12

Nixon, Mark. Feature Extraction & Image Processing for Computer Vision. 3rd ed. Burlington: Elsevier Science, 2012.

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13

Chaki, Jyotismita, and Nilanjan Dey. Texture Feature Extraction Techniques for Image Recognition. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-0853-0.

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14

Liu, Huan. Feature Extraction, Construction and Selection: A Data Mining Perspective. Boston, MA: Springer US, 1998.

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15

K, Kokula Krishna Hari, ed. Feature Extraction and Analysis of Breast Cancer Specimen: IJCST. India: Association of Scientists Developers and Faculties, 2013.

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16

Puig, Luis. Omnidirectional Vision Systems: Calibration, Feature Extraction and 3D Information. London: Springer London, 2013.

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17

Kyrki, Ville. Local and global feature extraction for invariant object recognition. Lappeenranta, Finland: Lappeenranta University of Technology, 2002.

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18

Supervised and unsupervised pattern recognition: Feature extraction and computational intelligence. Boca Raton, Fla: CRC Press, 2000.

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19

Joanis, Eric. Automatic verb classification using a general feature space. Ottawa: National Library of Canada, 2002.

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20

Wichert, Terry S. Feature based neural network acoustic transient signal classification. Monterey, Calif: Naval Postgraduate School, 1993.

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21

Brockdorff, Noellie. A feature-sampling theory of classification and recognition. Birmingham: University of Birmingham, 1998.

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22

Li, Jian. Synthetic aperture radar target detection, feature extraction, and image formation techniques. [Washington, DC: National Aeronautics and Space Administration, 1994.

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23

Okun, Oleg. Feature selection and ensemble methods for bioinformatics: Algorithmic classification and implementations. Hershey PA: Medical Information Science Reference, 2011.

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24

Zhang, Yanwu. Spectral feature classification of oceanographic processes using an autonomous underwater vehicle. Cambridge, Mass: Massachusetts Institute of Technology, 2000.

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25

Mokhlesabadifarahani, Bita, and Vinit Kumar Gunjan. EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction. Singapore: Springer Singapore, 2015. http://dx.doi.org/10.1007/978-981-287-320-0.

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26

Sabourin, Conrad. Optical character recognition and document segmentation: Character preprocessing, thinning, isolation, segmentation, feature extraction, cursive and multi-font recognition, writer/scriptor identification : bibliography. Montréal: Infolingua, 1994.

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27

Afanas'ev, Mihail, Mihail Bendikov, and Stanislav Korunov. Fundamentals of the economy of space activities. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1018193.

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The textbook describes in detail the classification of space goods and services, the segments and sectors of the global space market, the development prospects and the positioning of Russian enterprises in them. The methodological feature of the course consists in new approaches to the segmentation of the market and areas of space activities, identifying their deep relationships with the space industry. The practical side of the course is aimed at studying the methodology and practice of space project management, space pricing, organization of placement and execution of space government orders, and market analytics. The tutorial contains test questions for each chapter, test tasks, and a wide selection of topics for course design. The subject of the course papers is related to the specific activities of the enterprises of the space industry. Meets the requirements of the federal state educational standards of higher education of the latest generation. It is intended for third-year undergraduate and graduate students specializing in the field of training 38.03.01 and 38.04.01 "Economics" in the specialties "Economics of Space activities", "Economics of high-tech industries".

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28

K, Sharma R., Munish Kumar, Manish Kumar Jindal, Simpel Rani Jindal, and Anupam Garg. Feature Extraction and Classification Techniques for Text Recognition. IGI Global, 2020.

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29

K, Sharma R., Munish Kumar, Manish Kumar Jindal, Simpel Rani Jindal, and Anupam Garg. Feature Extraction and Classification Techniques for Text Recognition. IGI Global, 2020.

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30

Kumar, Munish. Feature Extraction and Classification Techniques for Text Recognition. IGI Global, 2020.

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31

K, Sharma R., Munish Kumar, Manish Kumar Jindal, Simpel Rani Jindal, and Anupam Garg. Feature Extraction and Classification Techniques for Text Recognition. IGI Global, 2020.

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32

K, Sharma R., Munish Kumar, Manish Kumar Jindal, Simpel Rani Jindal, and Anupam Garg. Feature Extraction and Classification Techniques for Text Recognition. IGI Global, 2020.

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33

Leong, Wai Yie. EEG Signal Processing: Feature extraction, selection and classification methods. The Institution of Engineering and Technology, 2019.

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34

Wai Yie Leong, ed. EEG Signal Processing: Feature extraction, selection and classification methods. Institution of Engineering and Technology, 2019. http://dx.doi.org/10.1049/pbhe016e.

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35

Das, Rik. Content-Based Image Classification: Efficient Machine Learning Using Robust Feature Extraction Techniques. Taylor & Francis Group, 2020.

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36

Content-Based Image Classification: Efficient Machine Learning Using Robust Feature Extraction Techniques. Taylor & Francis Group, 2020.

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37

Eyben, Florian. Real-time Speech and Music Classification by Large Audio Feature Space Extraction. Springer, 2018.

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38

Das, Rik. Content-Based Image Classification: Efficient Machine Learning Using Robust Feature Extraction Techniques. Taylor & Francis Group, 2020.

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39

Eyben, Florian. Real-time Speech and Music Classification by Large Audio Feature Space Extraction. Springer, 2017.

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40

Das, Rik. Content-Based Image Classification: Efficient Machine Learning Using Robust Feature Extraction Techniques. Taylor & Francis Group, 2020.

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41

Kumar, Nilesh, Nilesh Ramesh Kulkarni, and Vinayak Bairagi. EEG-Based Diagnosis of Alzheimer Disease: A Review and Novel Approaches for Feature Extraction and Classification Techniques. Elsevier Science & Technology Books, 2018.

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42

Grishman, Ralph. Information Extraction. Edited by Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0030.

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Information extraction (IE) is the automatic identification of selected types of entities, relations, or events in free text. This article appraises two specific strands of IE — name identification and classification, and event extraction. Conventional treatment of languages pays little attention to proper names, addresses etc. Presentations of language analysis generally look up words in a dictionary and identify them as nouns etc. The incessant presence of names in a text, makes linguistic analysis of the same difficult, in the absence of the names being identified by their types and as linguistic units. Name tagging involves creating, several finite-state patterns, each corresponding to some noun subset. Elements of the patterns would match specific/classes of tokens with particular features. Event extraction typically works by creating a series of regular expressions, customized to capture the relevant events. Enhancement of each expression is corresponded by a relevant, suitable enhancement in the event patterns.

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43

Masoud Nikravesh,Isabelle Guyon,Steve Gunn. Feature Extraction. Springer, 2008.

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44

Gunn, Steve, Isabelle Guyon, Masoud Nikravesh, and Lofti A. Zadeh. Feature Extraction: Foundations and Applications. Springer, 2016.

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45

Feature Extraction and Image Processing. Elsevier, 2002. http://dx.doi.org/10.1016/c2009-0-25049-5.

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46

Feature Extraction & Image Processing, Second Edition. Academic Press, 2007.

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47

Agarwal, Basant, and Namita Mittal. Prominent Feature Extraction for Sentiment Analysis. Springer, 2015.

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48

Hu, Li, and Zhiguo Zhang. EEG Signal Processing and Feature Extraction. Springer, 2019.

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49

Agarwal, Basant, and Namita Mittal. Prominent Feature Extraction for Sentiment Analysis. Springer, 2019.

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50

Nixon, Mark, and Alberto S. Aguado. Feature Extraction & Image Processing, Second Edition. 2nd ed. Academic Press, 2007.

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