Добірка наукової літератури з теми "Cyclist detection"
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Статті в журналах з теми "Cyclist detection"
Wang, Kelong, and Wei Zhou. "Pedestrian and cyclist detection based on deep neural network fast R-CNN." International Journal of Advanced Robotic Systems 16, no. 2 (March 1, 2019): 172988141982965. http://dx.doi.org/10.1177/1729881419829651.
Повний текст джерелаShahraki, Farideh Foroozandeh, Ali Pour Yazdanpanah, Emma E. Regentova, and Venkatesan Muthukumar. "A Trajectory Based Method of Automatic Counting of Cyclist in Traffic Video Data." International Journal on Artificial Intelligence Tools 26, no. 04 (August 2017): 1750015. http://dx.doi.org/10.1142/s0218213017500154.
Повний текст джерелаDrory, Ami, Hongdong Li, and Richard Hartley. "Estimating the projected frontal surface area of cyclists from images using a variational framework and statistical shape and appearance models." Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology 231, no. 3 (May 10, 2017): 169–83. http://dx.doi.org/10.1177/1754337117705489.
Повний текст джерелаAhmed, Sarfraz, M. Nazmul Huda, Sujan Rajbhandari, Chitta Saha, Mark Elshaw, and Stratis Kanarachos. "Pedestrian and Cyclist Detection and Intent Estimation for Autonomous Vehicles: A Survey." Applied Sciences 9, no. 11 (June 6, 2019): 2335. http://dx.doi.org/10.3390/app9112335.
Повний текст джерелаRadová, Zuzana, and Luboš Nouzovský. "Measuring of Cyclist Impact Dynamics." Applied Mechanics and Materials 821 (January 2016): 456–63. http://dx.doi.org/10.4028/www.scientific.net/amm.821.456.
Повний текст джерелаEddy, Chris, Christopher de Saxe, and David Cebon. "Camera-based measurement of cyclist motion." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233, no. 7 (August 7, 2018): 1793–805. http://dx.doi.org/10.1177/0954407018789301.
Повний текст джерелаJia, Enzo C., Jianqiang Wang, and Daiheng Ni. "An Efficient Methodology for Calibrating Traffic Flow Models Based on Bisection Analysis." Journal of Applied Mathematics 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/949723.
Повний текст джерелаJin, Wenqiang, Srinivasan Murali, Youngtak Cho, Huadi Zhu, Tianhao Li, Rachael Thompson Panik, Anika Rimu, et al. "CycleGuard." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5, no. 4 (December 27, 2021): 1–30. http://dx.doi.org/10.1145/3494992.
Повний текст джерелаNAMIHIRA, Yuki, Jun MIURA, and Shuji OISHI. "Pedestrian and cyclist detection by LIDAR-camera fusion." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2016 (2016): 2P2–07b4. http://dx.doi.org/10.1299/jsmermd.2016.2p2-07b4.
Повний текст джерелаS, Anjali, and Nithin Joe. "Faster RCNN for Concurrent Pedestrian and Cyclist Detection." International Journal of Electronics and Communication Engineering 5, no. 5 (May 25, 2018): 21–24. http://dx.doi.org/10.14445/23488549/ijece-v5i5p105.
Повний текст джерелаДисертації з теми "Cyclist detection"
De, Angelis Marco, Víctor Marín Puchades, Federico Fraboni, Luca Pietrantoni, and Gabriele Prati. "Negative attitudes towards cyclists influence the acceptance of an in-vehicle cyclist detection system." Elsevier, 2017. https://publish.fid-move.qucosa.de/id/qucosa%3A73236.
Повний текст джерелаHeydorn, Matthew Ryan. "Increased Cyclist Safety Using an Embedded System." BYU ScholarsArchive, 2019. https://scholarsarchive.byu.edu/etd/7391.
Повний текст джерелаBieshaar, Maarten [Verfasser]. "Cooperative intention detection using machine learning : advanced cyclist protection in the context of automated driving / Maarten Bieshaar." Kassel : kassel university press c/o Universität Kassel - Universitätsbibliothek, 2021. http://d-nb.info/1233244175/34.
Повний текст джерелаAbakar, Issakha Souleymane. "Algorithms for the detection and localization of pedestrians and cyclists using new generation automotive radar systems." Thesis, Rennes 1, 2017. http://www.theses.fr/2017REN1S159.
Повний текст джерелаIn response to the persistently high number of deaths provoked by road crashes, the automotive industry has promoted safety as a major topic in their global activity. Automotive radars have been transformed from being simple sensors for comfort vehicle, to becoming essential elements of safety standard. The design of new generations automotive radars has to face various constraints and generally proposes a compromise between reliability, robustness, manufacturability, high-performance and low cost. The main objective of this PhD thesis is to design algorithms for the detection and localization of pedestrians and cyclists using new generation automotive radars. We propose an optimal non-uniform antenna array architecture and some high resolution spectral estimation methods to accurately estimate the position of objects from the direction of arrival (DOA) of their responses to the radar. These techniques are adapted to the proposed antenna array architecture and the performance is evaluated using both simulated and real automotive radar data, acquired in the frame of specific scenarios. We propose a collision target detector, based on the orthogonality of angle-Doppler subspaces, whose main goal is to identify lateral targets, whose trajectory features represent potentially a danger of collision. A target attribute calculation method is also developed and classification algorithm is proposed to classify pedestrian, cyclists and vehicles. This classification algorithm is evaluated and validated using real automotive radar data with several scenarios
BAKKAL, Ahmet Tansu. "Acoustic Detection of Rear Approaching Vehicles for Cyclists." Thesis, Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-25182.
Повний текст джерелаSoames, Kieron, and Jonas Lind. "Detecting Cycles in GraphQL Schemas." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-156174.
Повний текст джерелаCronje, Mercia. "Engineering process model: Detection of cycles and determination of paths." Thesis, Stellenbosch : University of Stellenbosch, 2006. http://hdl.handle.net/10019.1/2376.
Повний текст джерелаIn order to plan the engineering work of large construction projects efficiently, a model of the engineering process is required. An engineering process can be modelled by sets of persons, tasks, datasets and tools, as well as the relationships between the elements of these sets. Tasks are more often than not dependent on other tasks in the engineering process. In large projects these dependencies are not easily recognised, and if tasks are not executed in the correct sequence, costly delays may occur. The homogeneous binary relation “has to be executed before” in the set of tasks can be used to determine the logical sequence of tasks algebraically. The relation can be described by a directed graph in the set of tasks, and the logical sequence of tasks can be determined by sorting the graph topologically, if the graph is acyclic. However, in an engineering process, this graph is not necessarily acyclic since certain tasks have to be executed in parallel, causing cycles in the graph. After generating the graph in the set of tasks, it is important to fuse all the cycles. This is achieved by finding the strongly connected components of the graph. The reduced graph, in which each strongly connected component is represented by a vertex, is a directed acyclic graph. The strongly connected components may be determined by different methods, including Kosaraju’s, Tarjan’s and Gabow’s methods. Considering the “has to be executed before” graph in the set of tasks, elementary paths through the graph, i.e. paths which do not contain any vertex more than once, are useful to investigate the influence of tasks on other tasks. For example, the longest elementary path of the graph is the logical critical path. The solution of such path problems in a network may be reduced to the solution of systems of equations using path algebras. The solution of the system of equations may be determined directly, i.e. through Gauss elimination, or iteratively, through Jacobi’s or Gauss-Seidel’s methods or the forward and back substitution method. The vertex sequence of an acyclic graph can be assigned in such a way that the coefficient matrix of the system of equations is reduced to staggered form, after which the solution is found by a simple back substitution. Since an engineering process has a start and an end, it is more acyclic than cyclic. Consequently we can usually reduce a substantial part of the coefficient matrix to staggered form. Using this technique, modifications of the solution methods mentioned above were implemented, and the efficiency of the technique is determined and compared between the various methods.
O'Connor, Matthew. "Ruminant prion disease detection and characterisation using protein misfolding cyclic amplification." Thesis, University of Nottingham, 2017. http://eprints.nottingham.ac.uk/41599/.
Повний текст джерелаKolluri, Murali Mohan. "Non-parametric nonlinearity detection under broadband excitation." University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1573224392534571.
Повний текст джерелаKalil, Haitham Fawzy Mohamed. "NANOMATERIALS-BASED SENSORS FOR PEROXYNITRITE DETECTION AND QUANTIFICATION." Cleveland State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=csu151336709631904.
Повний текст джерелаКниги з теми "Cyclist detection"
Conan, Doyle Arthur. The Adventure of the Solitary Cyclist. Mankato, MN, USA: Creative Education, 1991.
Знайти повний текст джерелаBob, Robbins. Signal investing: Detecting powerful trends in risk and market cycles. New York: McGraw-Hill, 2012.
Знайти повний текст джерелаPulido, Eugenio Fuentes. Contrarreloj. Barcelona, Spain: Tusquets, 2009.
Знайти повний текст джерелаGoodwin, Vincent. Sir Arthur Conan Doyle's The adventure of the solitary cyclist. Minneapolis, Minn: Magic Wagon, 2012.
Знайти повний текст джерелаMoody, Greg. Derailleur: A cycling murder mystery. Boulder, Colo: VeloPress, 1999.
Знайти повний текст джерелаDead air: A cycling murder mystery : a novel. Boulder, CO: VeloPress, 2002.
Знайти повний текст джерелаMoody, Greg. Deadroll: A cycling murder mystery. Boulder, Colo: VeloPress, 2001.
Знайти повний текст джерелаJohannes, Mark Robert Stephen. Detecting and understanding marine-terrestrial linkages in a developing watershed: Nutrient cycling in the Kenai River watershed. Anchorage, Alaska: EVOS Trustee Council, 2003.
Знайти повний текст джерелаConan, Doyle Arthur. Quatre aventures de Sherlock Holmes: La cycliste solitaire suivi de ; Charles Auguste Milverton ; Le Gloria Scott ; Le trois-quart aile manquant. Paris: Librio, 1994.
Знайти повний текст джерелаHill, Laban Carrick. Spiked snow. New York: Hyperion Books for Children, 1998.
Знайти повний текст джерелаЧастини книг з теми "Cyclist detection"
Saranya, Karattupalayam Chidambaram, Arunkumar Thangavelu, Ashwin Chidambaram, Sharan Arumugam, and Sushant Govindraj. "Cyclist Detection Using Tiny YOLO v2." In Advances in Intelligent Systems and Computing, 969–79. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0184-5_82.
Повний текст джерелаAhmed, Sarfraz, M. Nazmul Huda, Sujan Rajbhandari, Chitta Saha, Mark Elshaw, and Stratis Kanarachos. "Visual and Thermal Data for Pedestrian and Cyclist Detection." In Towards Autonomous Robotic Systems, 223–34. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-25332-5_20.
Повний текст джерелаLee, Vincent T. "Detection of Cyclic Dinucleotide Binding Proteins." In Microbial Cyclic Di-Nucleotide Signaling, 107–24. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-33308-9_7.
Повний текст джерелаWaters, Christopher M. "Methods for Cyclic Di-GMP Detection." In The Second Messenger Cyclic Di-GMP, 68–75. Washington, DC, USA: ASM Press, 2014. http://dx.doi.org/10.1128/9781555816667.ch6.
Повний текст джерелаDu, Xiao-Xia, and Xiao-Dong Su. "Detection of Cyclic Dinucleotides by STING." In c-di-GMP Signaling, 59–69. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-7240-1_6.
Повний текст джерелаXu, Wentao. "Detecting Targets Without Thermal Cycling in Food: Isothermal Amplification and Hybridization." In Functional Nucleic Acids Detection in Food Safety, 185–218. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-1618-9_10.
Повний текст джерелаJenner, Mareike. "Diversifying Detection: Proliferation of Channels and Television Cycles 1980–2000." In American TV Detective Dramas, 100–123. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/9781137425669_7.
Повний текст джерелаEldesokey, Abdelrahman, Michael Felsberg, and Fahad Shahbaz Khan. "Ellipse Detection for Visual Cyclists Analysis “In the Wild”." In Computer Analysis of Images and Patterns, 319–31. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64689-3_26.
Повний текст джерелаJiang, Di, Hui Liu, Qiang Guo, and Caiming Zhang. "Cyclic DenseNet for Tumor Detection and Identification." In Cyberspace Safety and Security, 487–93. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-37352-8_42.
Повний текст джерелаFrisén, Marianne. "Detection of Turning Points in Business Cycles." In International Encyclopedia of Statistical Science, 382–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_26.
Повний текст джерелаТези доповідей конференцій з теми "Cyclist detection"
Tian, Wei, and Martin Lauer. "Fast Cyclist Detection by Cascaded Detector and Geometric Constraint." In 2015 IEEE 18th International Conference on Intelligent Transportation Systems - (ITSC 2015). IEEE, 2015. http://dx.doi.org/10.1109/itsc.2015.211.
Повний текст джерелаBieshaar, Maarten, Stefan Zernetsch, Katharina Riepe, Konrad Doll, and Bernhard Sick. "Cyclist Motion State Forecasting - Going beyond Detection." In 2021 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2021. http://dx.doi.org/10.1109/ssci50451.2021.9660151.
Повний текст джерелаMasalov, Alexander, Pavel Matrenin, Jeffrey Ota, Florian Wirth, Christoph Stiller, Heath Corbet, and Eric Lee. "Specialized Cyclist Detection Dataset: Challenging Real-World Computer Vision Dataset for Cyclist Detection Using a Monocular RGB Camera." In 2019 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2019. http://dx.doi.org/10.1109/ivs.2019.8813814.
Повний текст джерелаXiaofei Li, Fabian Flohr, Yue Yang, Hui Xiong, Markus Braun, Shuyue Pan, Keqiang Li, and Dariu M. Gavrila. "A new benchmark for vision-based cyclist detection." In 2016 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2016. http://dx.doi.org/10.1109/ivs.2016.7535515.
Повний текст джерелаTong Li, Xianbin Cao, and Yanwu Xu. "An effective crossing cyclist detection on a moving vehicle." In 2010 8th World Congress on Intelligent Control and Automation (WCICA 2010). IEEE, 2010. http://dx.doi.org/10.1109/wcica.2010.5554979.
Повний текст джерелаAnnapareddy, Navya, Emir Sahin, Sander Abraham, Md Mofijul Islam, Max DePiro, and Tariq Iqbal. "A Robust Pedestrian and Cyclist Detection Method Using Thermal Images." In 2021 Systems and Information Engineering Design Symposium (SIEDS). IEEE, 2021. http://dx.doi.org/10.1109/sieds52267.2021.9483730.
Повний текст джерелаDu, Xiao-Ping, Hui Xiong, and Yang Li. "Have a Deep Look at Deformable Part Models for Cyclist Detection." In International Conference on Computer Science and Artificial Intelligence (CSAI2016). WORLD SCIENTIFIC, 2017. http://dx.doi.org/10.1142/9789813220294_0019.
Повний текст джерелаZernetsch, Stefan, Hannes Reichert, Viktor Kress, Konrad Doll, and Bernhard Sick. "A Holistic View on Probabilistic Trajectory Forecasting – Case Study. Cyclist Intention Detection." In 2022 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2022. http://dx.doi.org/10.1109/iv51971.2022.9827220.
Повний текст джерелаTyler-Rodrigue, Marco, and Richard Green. "Track Cyclist Detection and Identification using Mask R-CNN and K-means Clustering." In 2019 International Conference on Image and Vision Computing New Zealand (IVCNZ). IEEE, 2019. http://dx.doi.org/10.1109/ivcnz48456.2019.8961035.
Повний текст джерелаSaleh, Khaled, Mohammed Hossny, Ahmed Hossny, and Saeid Nahavandi. "Cyclist detection in LIDAR scans using faster R-CNN and synthetic depth images." In 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2017. http://dx.doi.org/10.1109/itsc.2017.8317599.
Повний текст джерелаЗвіти організацій з теми "Cyclist detection"
Kulhandjian, Hovannes. AI-based Pedestrian Detection and Avoidance at Night using an IR Camera, Radar, and a Video Camera. Mineta Transportation Institute, November 2022. http://dx.doi.org/10.31979/mti.2022.2127.
Повний текст джерелаCamarero, J. Developing New Tools for the in vivo Generation/Screening of Cyclic Peptide Libraries. A New Combinatorial Approach for the Detection of Bacterial Toxin Inhibitors. Office of Scientific and Technical Information (OSTI), November 2006. http://dx.doi.org/10.2172/902307.
Повний текст джерелаTesfaigzi, J., M. B. Wood, and N. F. Johnson. Expression of cyclin D{sub 1} during endotoxin-induced aleveolar type II cell hyperplasia in rat lung and the detection of apoptotic cells during the remodeling process. Office of Scientific and Technical Information (OSTI), December 1995. http://dx.doi.org/10.2172/381386.
Повний текст джерелаEngel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, July 1996. http://dx.doi.org/10.32747/1996.7613033.bard.
Повний текст джерела