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Libros sobre el tema "Lines detection and segmentation"

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Publicado: 25 de mayo de 2024

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1

Weiss, John. Automatic jet contrail detection and segmentation. [Washington, DC: National Aeronautics and Space Administration, 1997.

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2

Weiss, John. Automatic jet contrail detection and segmentation. [Washington, DC: National Aeronautics and Space Administration, 1997.

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3

Yang, Yi. Colour edge detection and segmentation using vector analysis. Ottawa: National Library of Canada, 1995.

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4

Rajalingam, Mallikka. Text Segmentation and Recognition for Enhanced Image Spam Detection. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-53047-1.

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5

Liang, Kung-Hao. From uncertainty to adaptivity: Multiscale edge detection and image segmentation. [s.l.]: typescript, 1997.

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6

Herout, Adam, Markéta Dubská y Jiří Havel. Real-Time Detection of Lines and Grids. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4414-4.

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7

Peterson, Jeffrey Shawn. Detection of downed trolley lines using arc signature analysis. Pittsburgh, PA: U.S. Dept. of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, Pittsburgh Research Center, 1997.

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8

K, Kokula Krishna Hari, ed. An Image Segmentation and Classification for Brain Tumor Detection using Pillar K-Means Algorithm. Chennai, India: Association of Scientists, Developers and Faculties, 2016.

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9

Don, Russell B. y IEEE Power Engineering Society. Power Engineering Education Committee., eds. Detection of downed conductors on utility distribution systems. Piscataway, NJ: Available from Publication Sales Dept., IEEE Service Center, 1989.

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10

Herout, Adam. Real-Time Detection of Lines and Grids: By PClines and Other Approaches. London: Springer London, 2013.

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11

Vavrik, Ursula. A priori and a posteriori travel market segmentation: Tailoring automatic interaction detection and cluster analysis for tourism marketing. Aix-en-Provence: Centre des Hautes Etudes Touristiques, 1990.

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12

Łukowicz, Mirosław. Metody wykrywania zwarć wysokooporowych w napowietrznych liniach elektroenergetycznych: Methods of high impedance fault detection in overhead electric power lines. Wrocław: Oficyna Wydawnicza Politechniki Wrocławskiej, 2013.

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13

Great Britain. Home Office. Policing and Reducing Crime Unit., ed. Reading between the lines: An evaluation of the Scientific Content Analysis technique (SCAN). London: Home Office Policing and Reducing Crime Unit, 2001.

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14

Zhong, Yuan. Image segmentation for defect detection on veneer surfaces. 1994.

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15

Wang, Xiaogang. Deep Learning in Object Recognition, Detection, and Segmentation. Now Publishers, 2016.

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16

Teutsch, Michael. Moving Object Detection and Segmentation for Remote Aerial Video Surveillance. Saint Philip Street Press, 2020.

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17

Moving Object Detection and Segmentation for Remote Aerial Video Surveillance. KIT Scientific Publishing, 2015.

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18

Teutsch, Michael. Moving Object Detection and Segmentation for Remote Aerial Video Surveillance. Saint Philip Street Press, 2020.

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19

Herout, Adam, Markéta Dubská y Jirí Havel. Real-Time Detection of Lines and Grids. Springer, 2012.

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20

Rajalingam, Mallikka. Text Segmentation and Recognition for Enhanced Image Spam Detection: An Integrated Approach. Springer International Publishing AG, 2021.

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21

Rajalingam, Mallikka. Text Segmentation and Recognition for Enhanced Image Spam Detection: An Integrated Approach. Springer International Publishing AG, 2020.

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22

Swift, Theodore N. Wiretap Detection Techniques: A Guide to Checking Telephone Lines. Thomas Investigative Pubns Inc, 2005.

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23

Swift, Theodore N. Wiretap Detection Techniques: A Guide to Checking Telephone Lines. Thomas Investigative Publications, Incorporat, 1997.

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24

Chan, Vincent Man Kin. Multiuser detection and spectrum balancing for digital subscriber lines. 2005.

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25

Zheng, Yefeng y Dorin Comaniciu. Marginal Space Learning for Medical Image Analysis: Efficient Detection and Segmentation of Anatomical Structures. Springer New York, 2016.

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26

Zheng, Yefeng y Dorin Comaniciu. Marginal Space Learning for Medical Image Analysis: Efficient Detection and Segmentation of Anatomical Structures. Springer, 2014.

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27

Marginal Space Learning for Medical Image Analysis: Efficient Detection and Segmentation of Anatomical Structures. Springer, 2014.

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28

Robust Filtering And Fault Detection Of Switched Delay Systems. Springer-Verlag Berlin and Heidelberg GmbH &, 2013.

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29

Realtime Detection Of Lines And Grids By Pclines And Other Approaches. Springer, 2012.

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30

Cheng, Liang y Sibel Pamukcu. Underground Sensing: Monitoring and Hazard Detection for Environment and Infrastructure. Elsevier Science & Technology Books, 2017.

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31

Underground Sensing: Monitoring and Hazard Detection for Environment and Infrastructure. Elsevier Science & Technology Books, 2017.

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32

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

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33

Advanced Deep Learning with TensorFlow 2 and Keras: Apply DL, GANs, VAEs, Deep RL, Unsupervised Learning, Object Detection and Segmentation, and More, 2nd Edition. Packt Publishing, Limited, 2020.

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34

Shiffrar, Maggie. The Aperture Problem. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780199794607.003.0076.

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The accurate visual perception of an object’s motion requires the simultaneous integration of motion information arising from that object along with the segmentation of motion information from other objects. When moving objects are seen through apertures, or viewing windows, the resultant illusions highlight some of the challenges that the visual system faces as it balances motion segmentation with motion integration. One example is the barber pole Illusion, in which lines appear to translate orthogonally to their true direction of emotion. Another is the illusory perception of incoherence when simple rectilinear objects translate or rotate behind disconnected apertures. Studies of these illusions suggest that visual motion processes frequently rely on simple form cues.
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35

Wigmans, Richard. Instrumental Aspects. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198786351.003.0005.

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This chapter deals with the practical aspects of designing, building and operating calorimeters. These aspects concern the structure of the detector (longitudinal and lateral segmentation, projective towers, hermeticity of 4π‎ devices), the readout of calorimeters based on detection of either light or charge signals, the operation in a magnetic field or at high luminosity, and the effects of radiation damage and how to deal with these. Also discussed are procedures for handling the signals, and using these to create triggers that may be used to select events of interest. Auxiliary equipment that may make such triggers more selective (preshower detectors, shower max detectors, etc.) is described as well.
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36

Bovens, Mark y Anchrit Wille. Education as a Cleavage. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198790631.003.0004.

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Cleavage formation in the nineteenth and twentieth century was based on religion and class. To what extent can we observe an emerging social and political cleavage along educational lines across Europe in the twenty-first century? We use a broad notion of cleavage and look at educational patterns of segmentation, stratification, and segregation; differences in political preferences; and to what extent these educational differences are reflected in the political landscape. We construct an index of cleavage formation that aims to measure to what extent the various differences along educational lines are merging. The degree to which the contours of this new divide have been crystallized is stronger in western and northern countries than elsewhere in Europe. This analysis forms the basis of our selection of six West European countries: the Netherlands, Belgium, Denmark, Germany, France, and the UK.
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37

Elkins, Evan. Locked Out. NYU Press, 2019. http://dx.doi.org/10.18574/nyu/9781479830572.001.0001.

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“This content is not available in your country.” Media consumers around the world regularly run into this reminder of geography’s imprint on digital culture. Despite utopian hopes of a borderless digital society in an era of globalization, DVDs, video games, and streaming platforms include digital rights management mechanisms like region codes and IP address detection systems that block media access within certain territories. Although propped up by national and transnational intellectual property regulation, these technologies of “regional lockout” are designed primarily to keep the entertainment industries’ global markets distinct. Beyond this, they frustrate consumers around the world and place certain territories on a hierarchy of global media access. Drawing on extensive research of media-industry strategies, consumer and retailer practices, and media regulation, Locked Out explores regional lockout in DVDs, console video games, and streaming video and music platforms. The book argues that regional lockout has shaped global media culture over the past few decades in three interrelated ways: as technological regulation, media distribution, and geocultural discrimination. As a form of digital rights management, regional lockout builds in limitations on the affordances of digital software and hardware. As distribution, it seeks to ensure that digital technologies accommodate media industries’ traditional segmentation of markets. Finally, as a cultural system, regional lockout shapes and reflects long-standing global hierarchies of power and discrimination.
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38

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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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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