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Artykuły w czasopismach na temat "Lines detection and segmentation"
Wang, Shengli, Zhangpeng Zhou i Wenbin Zhao. "Semantic Segmentation and Defect Detection of Aerial Insulators of Transmission Lines". Journal of Physics: Conference Series 2185, nr 1 (1.01.2022): 012086. http://dx.doi.org/10.1088/1742-6596/2185/1/012086.
Pełny tekst źródłaTao, Zhen, Shiwei Ren, Yueting Shi, Xiaohua Wang i Weijiang Wang. "Accurate and Lightweight RailNet for Real-Time Rail Line Detection". Electronics 10, nr 16 (23.08.2021): 2038. http://dx.doi.org/10.3390/electronics10162038.
Pełny tekst źródłaSong, Xiang, Xiaoyu Che, Huilin Jiang, Shun Yan, Ling Li, Chunxiao Ren i Hai Wang. "A Robust Detection Method for Multilane Lines in Complex Traffic Scenes". Mathematical Problems in Engineering 2022 (8.03.2022): 1–14. http://dx.doi.org/10.1155/2022/7919875.
Pełny tekst źródłaYan, Jichen, Xiaoguang Zhang, Siyang Shen, Xing He, Xuan Xia, Nan Li, Song Wang, Yuxuan Yang i Ning Ding. "A Real-Time Strand Breakage Detection Method for Power Line Inspection with UAVs". Drones 7, nr 9 (10.09.2023): 574. http://dx.doi.org/10.3390/drones7090574.
Pełny tekst źródłaXing, Junyao, Xiaojun Bi i Yu Weng. "A Multi-Scale Hybrid Attention Network for Sentence Segmentation Line Detection in Dongba Scripture". Mathematics 11, nr 15 (3.08.2023): 3392. http://dx.doi.org/10.3390/math11153392.
Pełny tekst źródłaChen, Yong, Yun-hui Wang, Song Li i Meng Li. "Transmission Line Instance Segmentation Algorithm Based on YOLACT". Journal of Physics: Conference Series 2562, nr 1 (1.08.2023): 012018. http://dx.doi.org/10.1088/1742-6596/2562/1/012018.
Pełny tekst źródłaLee, Jaehyun, Keunwoo Lee, Jaewon Yang, Young-Jin Kim i Seung-Woo Kim. "Comb segmentation spectroscopy for rapid detection of molecular absorption lines". Optics Express 27, nr 6 (13.03.2019): 9088. http://dx.doi.org/10.1364/oe.27.009088.
Pełny tekst źródłaZhu, Yuhang, Zhezhuang Xu, Ye Lin, Dan Chen, Zhijie Ai i Hongchuan Zhang. "A Multi-Source Data Fusion Network for Wood Surface Broken Defect Segmentation". Sensors 24, nr 5 (2.03.2024): 1635. http://dx.doi.org/10.3390/s24051635.
Pełny tekst źródłaCheng, Wangfeng, Xuanyao Wang i Bangguo Mao. "Research on Lane Line Detection Algorithm Based on Instance Segmentation". Sensors 23, nr 2 (10.01.2023): 789. http://dx.doi.org/10.3390/s23020789.
Pełny tekst źródłaTang, Yang Shan, Dao Hua Xia, Gui Yang Zhang, Li Na Ge i Xin Yang Yan. "The Detection Method of Lane Line Based on the Improved Otsu Threshold Segmentation". Applied Mechanics and Materials 741 (marzec 2015): 354–58. http://dx.doi.org/10.4028/www.scientific.net/amm.741.354.
Pełny tekst źródłaRozprawy doktorskie na temat "Lines detection and segmentation"
Li, Yaqian. "Image segmentation and stereo vision matching based on declivity line : application for vehicle detection". Thesis, Rouen, INSA, 2010. http://www.theses.fr/2010ISAM0010.
Pełny tekst źródłaIn the framework of driving assistance systems, we contributed to stereo vision approaches for edge extraction, matching of stereoscopic pair of images and vehicles detection. Edge extraction is performed based on the concept of declivity line we introduced. Declivity line is constructed by connecting declivities according to their relative position and intensity similarity. Edge extraction is obtained by filtering constructed declivity lines based on their characteristics. Experimental results show that declivity line method extracts additional useful information compared to declivity operator which filtered them out. Edge points of declivity lines are then matched using dynamic programming, and characteristics of declivity line reduce the number of false matching. In our matching method, declivity line contributes to detailed reconstruction of 3D scene. Finally, symmetrical characteristic of vehicles are exploited as a criterion for their detection. To do so, we extend the monocular concept of symmetry map to stereo concept. Consequently, by performing vehicle detection on disparity map, a (axis; width; disparity) symmetry map is constructed instead of an (axis; width) symmetry map. In our stereo concept, obstacles are examined at different depths thus avoiding disturbance of complex scene from which monocular concept suffers
Bonakdar, Sakhi Omid. "Segmentation of heterogeneous document images : an approach based on machine learning, connected components analysis, and texture analysis". Phd thesis, Université Paris-Est, 2012. http://tel.archives-ouvertes.fr/tel-00912566.
Pełny tekst źródłaKhairallah, Mahmoud. "Flow-Based Visual-Inertial Odometry for Neuromorphic Vision Sensors". Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPAST117.
Pełny tekst źródłaRather than generating images constantly and synchronously, neuromorphic vision sensors -also known as event-based cameras- permit each pixel to provide information independently and asynchronously whenever brightness change is detected. Consequently, neuromorphic vision sensors do not encounter the problems of conventional frame-based cameras like image artifacts and motion blur. Furthermore, they can provide lossless data compression, higher temporal resolution and higher dynamic range. Hence, event-based cameras conveniently replace frame-based cameras in robotic applications requiring high maneuverability and varying environmental conditions. In this thesis, we address the problem of visual-inertial odometry using event-based cameras and an inertial measurement unit. Exploiting the consistency of event-based cameras with the brightness constancy conditions, we discuss the availability of building a visual odometry system based on optical flow estimation. We develop our approach based on the assumption that event-based cameras provide edge-like information about the objects in the scene and apply a line detection algorithm for data reduction. Line tracking allows us to gain more time for computations and provides a better representation of the environment than feature points. In this thesis, we do not only show an approach for event-based visual-inertial odometry but also event-based algorithms that can be used as stand-alone algorithms or integrated into other approaches if needed
Wigington, Curtis Michael. "End-to-End Full-Page Handwriting Recognition". BYU ScholarsArchive, 2018. https://scholarsarchive.byu.edu/etd/7099.
Pełny tekst źródłaTorr, Philip Hilaire Sean. "Motion segmentation and outlier detection". Thesis, University of Oxford, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.308173.
Pełny tekst źródłaDeng, Jingjing (Eddy). "Adaptive learning for segmentation and detection". Thesis, Swansea University, 2017. https://cronfa.swan.ac.uk/Record/cronfa36297.
Pełny tekst źródłaHastings, Joseph R. 1980. "Incremental Bayesian segmentation for intrusion detection". Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/28399.
Pełny tekst źródłaIncludes bibliographical references (leaves 131-133).
This thesis describes an attempt to monitor patterns of system calls generated by a Unix host in order to detect potential intrusion attacks. Sequences of system calls generated by privileged processes are analyzed using incremental Bayesian segmentation in order to detect anomalous activity. Theoretical analysis of various aspects of the algorithm and empirical analysis of performance on synthetic data sets are used to tune the algorithm for use as an Intrusion Detection System.
by Joseph R. Hastings.
M.Eng.
Nedilko, Bohdan. "Seismic detection of rockfalls on railway lines". Thesis, University of British Columbia, 2016. http://hdl.handle.net/2429/58097.
Pełny tekst źródłaScience, Faculty of
Earth, Ocean and Atmospheric Sciences, Department of
Graduate
Torrent, Palomeras Albert. "Simultaneous detection and segmentation for generic objects". Doctoral thesis, Universitat de Girona, 2013. http://hdl.handle.net/10803/117736.
Pełny tekst źródłaEn aquesta tesi s'estudia la detecció i segmentació simultània d'objectes genèrics en imatges. La proposta està basada en un diccionari de parts de l'objecte que el defineixen i, alhora, ens permet extreure les característiques de detecció i segmentació per entrenar el classificador. A més, dins l'entrenament del classificador s'inclou la possibilitat de creuar informació entre la detecció i la segmentació, de tal manera que una bona detecció pugui ajudar a segmentar i viceversa. L'algorisme s'ha validat adaptant-lo al reconeixement d'objectes en imatge mèdica i imatge astronòmica. Aquest punt reforça el principal objectiu de la tesi: proposar un sistema genèric capaç de tractar amb objectes de qualsevol tipus de naturalesa
HEGSTAM, BJÖRN. "Defect detection and segmentation inmultivariate image streams". Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-142069.
Pełny tekst źródłaOptoNova är en världsledande leverantör av inspektionssystem for kvalitetskontroll av ytor och kanter i hög hastighet. Företaget utvecklar egna sensorsystem och mjukvara, och är intresserade av att undersöka möjligheten att bättre utnyttja tillgänglig sensordata genom att använda metoder baserade på maskininlärning. Syftet med det här projektet var att utveckla en metod för att upptäcka ytdefekter i multivariata bilder. Ett tidigare examensarbete gjort hos OptoNova visade på lovande resultat vid inspektion av kanter på köksluckor. Modellen som utvecklades i det projektet använde sig av ett Difference of Gaussians-skalrum. Den modellen användes som utgångspunkt för det här arbetet med vissa förändringar gjorda för att lägga fokus på texturdefekter i plana ytor. Den utvecklade modellen tar in en multivariat bild och genererar en Laplacepyramid. Varje nivå i pyramiden skickas sedan igenom en tränad bildmodell som i sin tur producerar en gråskalebild där möjliga defekter är markerade. Samtliga bildmodellers resultat skalas upp till samma storlek som ursprungsbilden och en medelvärdesbild beräknas. Detta ger den slutliga defektbilden som visar vilka delar av det inlästa provet som är defekta. Varje bildmodell består dels av en modul som extraherar särdragsvektorer och dels av en modul som modellerar hur vektorer från oskadade ytor är fördelade i rummet av särdragsvektorer. För det senare användes en Gaussian mixture model (GMM). Modellens modullära design gör det enkelt att använda olika typer av särdragsvektorer och modeller för dessa. Tester visade att pyramidmodellen kan prestera bättre än den tidigare utvecklade modellen. Utmärkta resultat uppnåddes vid detektion av defekter som karaktäriserades av tydliga avvikelser i textur. Defekter som däremot endast utgjordes av mindre variationer i intensitet hittades generellt sett inte. Det konstaterades att den nya modellen visar på potential till att fungera väl, men att mer arbete fortfarande behöver göras. Framförallt måste fler tester göras med fler prover, samt prover med varierande ytmönster, såsom träytor.
Książki na temat "Lines detection and segmentation"
Weiss, John. Automatic jet contrail detection and segmentation. [Washington, DC: National Aeronautics and Space Administration, 1997.
Znajdź pełny tekst źródłaWeiss, John. Automatic jet contrail detection and segmentation. [Washington, DC: National Aeronautics and Space Administration, 1997.
Znajdź pełny tekst źródłaYang, Yi. Colour edge detection and segmentation using vector analysis. Ottawa: National Library of Canada, 1995.
Znajdź pełny tekst źródłaRajalingam, 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.
Pełny tekst źródłaLiang, Kung-Hao. From uncertainty to adaptivity: Multiscale edge detection and image segmentation. [s.l.]: typescript, 1997.
Znajdź pełny tekst źródłaHerout, Adam, Markéta Dubská i Jiří Havel. Real-Time Detection of Lines and Grids. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4414-4.
Pełny tekst źródłaPeterson, 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.
Znajdź pełny tekst źródłaK, Kokula Krishna Hari, red. An Image Segmentation and Classification for Brain Tumor Detection using Pillar K-Means Algorithm. Chennai, India: Association of Scientists, Developers and Faculties, 2016.
Znajdź pełny tekst źródłaDon, Russell B., i IEEE Power Engineering Society. Power Engineering Education Committee., red. Detection of downed conductors on utility distribution systems. Piscataway, NJ: Available from Publication Sales Dept., IEEE Service Center, 1989.
Znajdź pełny tekst źródłaHerout, Adam. Real-Time Detection of Lines and Grids: By PClines and Other Approaches. London: Springer London, 2013.
Znajdź pełny tekst źródłaCzęści książek na temat "Lines detection and segmentation"
Abdelfattah, Rabab, Xiaofeng Wang i Song Wang. "TTPLA: An Aerial-Image Dataset for Detection and Segmentation of Transmission Towers and Power Lines". W Computer Vision – ACCV 2020, 601–18. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69544-6_36.
Pełny tekst źródłaRuss, John C. "Segmentation of Edges and Lines". W Computer-Assisted Microscopy, 71–98. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4613-0563-7_4.
Pełny tekst źródłaMartino, J. C., i Salvatore Tabbone. "Detection of Lofar lines". W Image Analysis and Processing, 709–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/3-540-60298-4_336.
Pełny tekst źródłaLu, Tong, Shivakumara Palaiahnakote, Chew Lim Tan i Wenyin Liu. "Character Segmentation and Recognition". W Video Text Detection, 145–68. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-6515-6_6.
Pełny tekst źródłaGauch, John M. "Segmentation and edge detection". W The Colour Image Processing Handbook, 163–87. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5779-1_9.
Pełny tekst źródłaHariharan, Bharath, Pablo Arbeláez, Ross Girshick i Jitendra Malik. "Simultaneous Detection and Segmentation". W Computer Vision – ECCV 2014, 297–312. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10584-0_20.
Pełny tekst źródłaMorel, Jean Michel, i Sergio Solimini. "Edge Detection and Segmentation". W Variational Methods in Image Segmentation, 3–7. Boston, MA: Birkhäuser Boston, 1995. http://dx.doi.org/10.1007/978-1-4684-0567-5_1.
Pełny tekst źródłaHogan, Ciarán, i Ganesh Sistu. "Automatic Vehicle Ego Body Extraction for Reducing False Detections in Automated Driving Applications". W Communications in Computer and Information Science, 264–75. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-26438-2_21.
Pełny tekst źródłaRajalingam, Mallikka. "Character Segmentation". W Text Segmentation and Recognition for Enhanced Image Spam Detection, 55–70. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-53047-1_4.
Pełny tekst źródłaDharanipragada, S., M. Franz, J. S. McCarley, T. Ward i W. J. Zhu. "Segmentation and Detection at IBM". W Topic Detection and Tracking, 135–48. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0933-2_7.
Pełny tekst źródłaStreszczenia konferencji na temat "Lines detection and segmentation"
Zhu, Donglin, Lei Li, Rui Guo i Shifan Zhan. "Fault Detection by Using Instance Segmentation". W International Petroleum Technology Conference. IPTC, 2021. http://dx.doi.org/10.2523/iptc-21249-ms.
Pełny tekst źródłaKumar, Rajiv, i Amardeep Singh. "Detection and segmentation of lines and words in Gurmukhi handwritten text". W 2010 IEEE 2nd International Advance Computing Conference (IACC 2010). IEEE, 2010. http://dx.doi.org/10.1109/iadcc.2010.5422927.
Pełny tekst źródłaXue, Chuhui, Shijian Lu i Wei Zhang. "MSR: Multi-Scale Shape Regression for Scene Text Detection". W Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/139.
Pełny tekst źródłaKavallieratou, Ergina. "Text line detection and segmentation". W the 2010 ACM Symposium. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1774088.1774102.
Pełny tekst źródłaJahan, Kanwal, Jeethesh Pai Umesh i Michael Roth. "Anomaly Detection on the Rail Lines Using Semantic Segmentation and Self-supervised Learning". W 2021 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2021. http://dx.doi.org/10.1109/ssci50451.2021.9659920.
Pełny tekst źródłaHota, Manjit, Sudarshan Rao B i Uttam Kumar. "Power Lines Detection and Segmentation In Multi-Spectral Uav Images Using Convolutional Neural Network". W 2020 IEEE India Geoscience and Remote Sensing Symposium (InGARSS). IEEE, 2020. http://dx.doi.org/10.1109/ingarss48198.2020.9358967.
Pełny tekst źródłaEl-merabet, Y., C. Meurie, Y. Ruichek, A. Sbihi i R. Touahni. "Watershed regions and watershed lines based cooperation strategy for image segmentation. Application to roof detection". W 2011 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT). IEEE, 2011. http://dx.doi.org/10.1109/isspit.2011.6151594.
Pełny tekst źródłaPeng, Yaqin, Xin Zhang, Dandan Li, Yifei Chen i Yi Shen. "An Infusion Liquid Level Detection Method Based on Improved ROI Segmentation and Horizontal Lines Modification". W 2022 41st Chinese Control Conference (CCC). IEEE, 2022. http://dx.doi.org/10.23919/ccc55666.2022.9902495.
Pełny tekst źródłaProtschky, Valentin, Paul Seifert i Stefan Feit. "Stop Line Detection Using Satellite-Image Segmentation". W 2015 IEEE 81st Vehicular Technology Conference (VTC Spring). IEEE, 2015. http://dx.doi.org/10.1109/vtcspring.2015.7146110.
Pełny tekst źródłaPeter, Rebekka, Yuduo Song i Martin Lauer. "Efficient Ego Lane Detection for Various Lane Types". W Forum Bildverarbeitung 2020. KIT Scientific Publishing, 2020. http://dx.doi.org/10.58895/ksp/1000124383-33.
Pełny tekst źródłaRaporty organizacyjne na temat "Lines detection and segmentation"
Hazi, A. Radiation Detection Center on the Front Lines. Office of Scientific and Technical Information (OSTI), wrzesień 2005. http://dx.doi.org/10.2172/885122.
Pełny tekst źródłaBajcsy, Ruzena, Sang W. Lee i Ales Leonardis. Image Segmentation with Detection of Highlights and Inter-Reflections Using Color. Fort Belvoir, VA: Defense Technical Information Center, czerwiec 1989. http://dx.doi.org/10.21236/ada218710.
Pełny tekst źródłaAsari, Vijayan, Paheding Sidike, Binu Nair, Saibabu Arigela, Varun Santhaseelan i Chen Cui. PR-433-133700-R01 Pipeline Right-of-Way Automated Threat Detection by Advanced Image Analysis. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), grudzień 2015. http://dx.doi.org/10.55274/r0010891.
Pełny tekst źródłaWang, Ting-Wei, Yun-Hsuan Tzeng, Jia-Sheng Hong, Ho-Ren Liu, Kuan-Ting Wu, Huan-Yu Hsu, Hao-Neng Fu, Yung-Tsai Lee, Wei-Hsian Yin i Yu-Te Wu. Systematic Review and Meta-Analysis of Aortic Dissection Diagnosis via CT: Evaluating Deep Learning for Detection Against Expert Analysis and Its Application in Detection and Segmentation. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, marzec 2024. http://dx.doi.org/10.37766/inplasy2024.3.0125.
Pełny tekst źródłaKlobucar, Blaz. Urban Tree Detection in Historical Aerial Imagery of Sweden : a test in automated detection with open source Deep Learning models. Faculty of Landscape Architecture, Horticulture and Crop Production Science, Swedish University of Agricultural Sciences, 2024. http://dx.doi.org/10.54612/a.7kn4q7vikr.
Pełny tekst źródłaWang, Ting-Wei, Yun-Hsuan Tzeng, Jia-Sheng Hong, Ho-Ren Liu, Kuan-Ting Wu, Huan-Yu Hsu, Hao-Neng Fu, Yung-Tsai Lee, Wei-Hsian Yin i Yu-Te Wu. The Role of Deep Learning in Aortic Aneurysm Segmentation and Detection from CT Scans: A Systematic Review and Meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, marzec 2024. http://dx.doi.org/10.37766/inplasy2024.3.0126.
Pełny tekst źródłaAlhasson, Haifa F., i Shuaa S. Alharbi. New Trends in image-based Diabetic Foot Ucler Diagnosis Using Machine Learning Approaches: A Systematic Review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, listopad 2022. http://dx.doi.org/10.37766/inplasy2022.11.0128.
Pełny tekst źródłaCheng, Peng, James V. Krogmeier, Mark R. Bell, Joshua Li i Guangwei Yang. Detection and Classification of Concrete Patches by Integrating GPR and Surface Imaging. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317320.
Pełny tekst źródłaCheng, Peng, James V. Krogmeier, Mark R. Bell, Joshua Li i Guangwei Yang. Detection and Classification of Concrete Patches by Integrating GPR and Surface Imaging. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317320.
Pełny tekst źródłaRau, Jerry. PR-542-163745-R01 Defining Close Metal Object Detection Capabilities of MFL ILI Tools. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), wrzesień 2017. http://dx.doi.org/10.55274/r0011422.
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