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Books on the topic 'Detection feature'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Barbieri, Gillian Sylvia Anna-Stasia. The role of spatial derivatives in feature detection. University of Birmingham, 2000.

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2

Zhang, Zhifen, Guangrui Wen, and Wenjing Ren. Multiple Sensing-Driven Feature Extraction and Defect Detection. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-4808-5.

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3

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

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4

United States. National Aeronautics and Space Administration., ed. Synthetic aperture radar target detection, feature extraction, and image formation techniques. National Aeronautics and Space Administration, 1994.

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5

Neelanarayanan, ed. Feature Analysis for Abnormality Detection in Breast Thermogram Sequences Subject to Cold Stress. Association of Scientists, Developers and Faculties, 2014.

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6

Levin, Boris. Seĭsmichnostʹ Tikhookeanskogo regiona: Vyi︠a︡vlenie globalʹnykh zakonomernosteĭ = Seismicity of the Pacific Region : global feature detection. "I︠A︡nus-K", 2012.

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7

L, Jankovsky Amy, and Lewis Research Center, eds. Real-time sensor validation, signal reconstruction, and feature detection for an RLV propulsion testbed. National Aeronautics and Space Administration, Lewis Research Center, 1998.

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8

L, Jankovsky Amy, and Lewis Research Center, eds. Real-time sensor validation, signal reconstruction, and feature detection for an RLV propulsion testbed. National Aeronautics and Space Administration, Lewis Research Center, 1998.

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9

L, Jankovsky Amy, and Lewis Research Center, eds. Real-time sensor validation, signal reconstruction, and feature detection for an RLV propulsion testbed. National Aeronautics and Space Administration, Lewis Research Center, 1998.

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10

L, Jankovsky Amy, and Lewis Research Center, eds. Real-time sensor validation, signal reconstruction, and feature detection for an RLV propulsion testbed. National Aeronautics and Space Administration, Lewis Research Center, 1998.

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11

David, Lane, and United States. National Aeronautics and Space Administration., eds. Enhanced line integral convolution with flow feature detection: NAS technical report NAS-96-007. National Aeronautics and Space Administration, 1996.

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12

Ruppell, Tanya J. Detecting feature contrast in images. National Library of Canada, 2001.

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13

Rand, Robert S. A hybrid methodology for detecting cartographically significant features using Landsat TM imagery. U.S. Army Corps of Engineers, Engineer Topographic Laboratories, 1991.

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14

Anderson, Charles E. "An investigation of the detection of tornadic thunderstorms by observing storm top features using geosynchronous satellite imagery". Dept. of Marine, Earth and Atmospheric Sciences, North Carolina State University, 1991.

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15

Anderson, Charles E. "An investigation of the detection of tornadic thunderstorms by observing storm top features using geosynchronous satellite imagery". Dept. of Marine, Earth and Atmospheric Sciences, North Carolina State University, 1991.

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16

Kouresh, Danai, Lewicki David G, and United States. National Aeronautics and Space Administration., eds. Unsupervised pattern classifier for abnormality-scaling of vibration features for helicopter gearbox fault diagnosis. National Aeronautics and Space Administration, 1996.

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17

Jacob, Irène. Red. Miramax Home Entertainment, 1994.

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18

Canning, Victor. Birds of a feather. Morrow, 1985.

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19

Canning, Victor. Birds of a feather. Ulverscroft, 2012.

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20

Canning, Victor. Birds of a feather. Morrow, 1985.

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21

Canning, Victor. Birds of a feather. Heinemann, 1985.

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22

Metternicht, Graciela Isabel. Detecting and monitoring land degradation features and processes in the Cochabamba valleys, Bolivia: A synergistic approach. International Institute for Aerospace Survey and Earth Science, 1996.

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23

Oganes︠i︡an, Karen. Domovoĭ. RBC Video (distributor), 2008.

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24

Liang, Caiyuan. Sheng shi Renjie: The greatness of a hero. Tai sheng yu le gong si, 2009.

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25

Dixon, Franklin W. The Yellow Feather Mystery. Penguin USA, Inc., 2009.

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26

Murphy, Elspeth Campbell. The mystery of the eagle feather. Bethany House Publishers, 1995.

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27

Winspear, Jacqueline. Birds of a feather. Soho Press, 2004.

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28

The Open The Open Courses Library. Smile Identification Via Feature Recognition and Corner Detection. Independently Published, 2019.

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29

Patra, Prasenjit Kr, Nilanjan Dey, and Amira Ashour. Feature Detectors and Motion Detection in Video Processing. IGI Global, 2016.

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30

Li, Yuxing, and Luca Fredianelli, eds. Detection and Feature Extraction in Acoustic Sensor Signals. MDPI, 2023. http://dx.doi.org/10.3390/books978-3-0365-9190-2.

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31

Nguyen, Duy Phuc. An FPGA implementation of face detection and lip feature extraction. 2005.

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32

Kim, Kwangjo, Muhamad Erza Aminanto, and Harry Chandra Tanuwidjaja. Network Intrusion Detection using Deep Learning: A Feature Learning Approach. Springer, 2018.

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33

Nguyen, Duy Phuc. An FPGA implementation of face detection and lip feature extraction. 2005.

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34

Kim, Kwangjo, Muhamad Erza Aminanto, and Harry Chandra Tanuwidjaja. Network Intrusion Detection using Deep Learning: A Feature Learning Approach. Springer, 2018.

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35

Lee, Jimmy Kim-Mil. ECG feature extraction without fiducial detection: Applications to ECG biometric recognition. 2006.

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36

Pierce, Linda. AN3377 - Using the Undervoltage Lockout Detection Feature on SPI Serial EEPROMs. Microchip Technology Incorporated, 2020.

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37

Detection and Feature Extraction of Mine-Like Objects from Seismic Sonar Signals. Storming Media, 2001.

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38

Tari, Zahir, Adil Fahad, Abdulmohsen Almalawi, and Xun Yi. Network Classification for Traffic Management: Anomaly detection, feature selection, clustering and classification. Institution of Engineering and Technology, 2020. http://dx.doi.org/10.1049/pbpc032e.

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39

Tari, Zahir, Adil Fahad, Abdulmohsen Almalawi, and Xun Yi. Network Classification for Traffic Management: Anomaly Detection, Feature Selection, Clustering and Classification. Institution of Engineering & Technology, 2020.

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40

Combined optimization of image-gathering and image-processing systems for scene feature detection. National Aeronautics and Space Administration, Langley Research Center, 1987.

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41

Pal, Saurabh, and Swanirbhar Majumder. Time Plane, Feature Extraction of ECG wave and Abnormality Detection: With MATLAB program. LAP LAMBERT Academic Publishing, 2012.

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42

Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments. MDPI, 2021. http://dx.doi.org/10.3390/books978-3-0365-1269-3.

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43

Woźniak, Marcin. Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments. Mdpi AG, 2021.

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44

National Aeronautics and Space Administration (NASA) Staff. Real-Time Sensor Validation, Signal Reconstruction, and Feature Detection for an RLV Propulsion Testbed. Independently Published, 2018.

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45

Beninger, Richard J. Neuroanatomy and dopamine systems. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198824091.003.0011.

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Neuroanatomy and dopamine systems explains how sensory signals ascend the central nervous system via a series of nuclei; axons detecting specific elements converge onto higher-order neurons that respond to particular stimulus features. Assemblies of feature-detection cells in the cerebral cortex detect complex stimuli such as faces. These cell assemblies project to motor nuclei of the dorsal and ventral striatum where they terminate on dendritic spines of efferent medium spiny neurons. Dopaminergic projections from ventral mesencephalic nuclei terminate on the same spines. Individual corticost

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46

Leibo, Joel Z., and Tomaso Poggio. Perception. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199674923.003.0025.

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This chapter provides an overview of biological perceptual systems and their underlying computational principles focusing on the sensory sheets of the retina and cochlea and exploring how complex feature detection emerges by combining simple feature detectors in a hierarchical fashion. We also explore how the microcircuits of the neocortex implement such schemes pointing out similarities to progress in the field of machine vision driven deep learning algorithms. We see signs that engineered systems are catching up with the brain. For example, vision-based pedestrian detection systems are now a

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47

Demian. Detective Smoothies: Feature Movie Script by Demian. Independently Published, 2021.

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48

Klein, Günter. Campylobacter: Features, Detection, and Prevention of Foodborne Disease. Elsevier Science & Technology Books, 2016.

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49

Klein, Günter. Campylobacter: Features, Detection, and Prevention of Foodborne Disease. Elsevier Science & Technology Books, 2016.

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50

Chan, Paul K. S., Hoi-shan Kwan, and Martin C. W. Chan. Norovirus: Features, Detection and Prevention of Foodborne Disease. Elsevier Science & Technology Books, 2016.

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