Academic literature on the topic 'Crowd Analysi'
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Journal articles on the topic "Crowd Analysi"
Andriyanto, Sidhiq, M. Suyanto, and Sukoco Sukoco. "Implementasi Metode Reynolds menggunakan Simulasi Kerumunan Bebek." INTENSIF 1, no. 2 (August 21, 2017): 75. http://dx.doi.org/10.29407/intensif.v1i2.788.
Full textBhuiyan, Roman, Junaidi Abdullah, Noramiza Hashim, Fahmid Al Farid, Wan Noorshahida Mohd Isa, Jia Uddin, and Norra Abdullah. "Deep Dilated Convolutional Neural Network for Crowd Density Image Classification with Dataset Augmentation for Hajj Pilgrimage." Sensors 22, no. 14 (July 7, 2022): 5102. http://dx.doi.org/10.3390/s22145102.
Full textAiello, Lucia. "Digital Skill Evolution in an Industrial Relationship." International Journal of R&D Innovation Strategy 1, no. 1 (January 2019): 1–15. http://dx.doi.org/10.4018/ijrdis.2019010101.
Full textHusman, Muhammad Afif, Waleed Albattah, Zulkifli Zainal Abidin, Yasir Mohd Mustafah, Kushsairy Kadir, Shabana Habib, Muhammad Islam, and Sheroz Khan. "Unmanned Aerial Vehicles for Crowd Monitoring and Analysis." Electronics 10, no. 23 (November 29, 2021): 2974. http://dx.doi.org/10.3390/electronics10232974.
Full textR, Shaamili. "A Research Perceptive on Deep Learning Framework for Pedestrian Detection in a Crowd." Computational Intelligence and Machine Learning 3, no. 2 (October 14, 2022): 9–14. http://dx.doi.org/10.36647/ciml/03.02.a002.
Full textElbishlawi, Sherif, Mohamed H. Abdelpakey, Agwad Eltantawy, Mohamed S. Shehata, and Mostafa M. Mohamed. "Deep Learning-Based Crowd Scene Analysis Survey." Journal of Imaging 6, no. 9 (September 11, 2020): 95. http://dx.doi.org/10.3390/jimaging6090095.
Full textBorch, Christian. "Body to Body: On the Political Anatomy of Crowds." Sociological Theory 27, no. 3 (September 2009): 271–90. http://dx.doi.org/10.1111/j.1467-9558.2009.01348.x.
Full textMalhotra, Arvind, and Ann Majchrzak. "Greater associative knowledge variety in crowdsourcing platforms leads to generation of novel solutions by crowds." Journal of Knowledge Management 23, no. 8 (October 14, 2019): 1628–51. http://dx.doi.org/10.1108/jkm-02-2019-0094.
Full textObbo, Aggrey, Pius Ariho, and Evarist Nabaasa. "Towards People Crowd Detection Using Wireless Sensor Networks." European Journal of Technology 6, no. 2 (June 17, 2022): 32–48. http://dx.doi.org/10.47672/ejt.1071.
Full textYugendar, Poojari, and K. V. R. Ravishankar. "Crowd Behavioural Analysis at a Mass Gathering Event." Journal of KONBiN 46, no. 1 (June 1, 2018): 5–20. http://dx.doi.org/10.2478/jok-2018-0020.
Full textDissertations / Theses on the topic "Crowd Analysi"
Bisagno, Niccolò. "On simulating and predicting pedestrian trajectories in a crowd." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/256722.
Full textMehran, Ramin. "Analysis of behaviors in crowd videos." Doctoral diss., University of Central Florida, 2011. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4801.
Full textID: 031001560; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Title from PDF title page (viewed August 26, 2013).; Thesis (Ph.D.)--University of Central Florida, 2011.; Includes bibliographical references (p. 100-104).
Ph.D.
Doctorate
Electrical Engineering and Computer Science
Engineering and Computer Science
Electrical Engineering
Holmer, Torsten, and Jörg Rainer Noennig. "Listening to the Crowd." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-234390.
Full textHolmer, Torsten, and Jörg Rainer Noennig. "Listening to the Crowd." TUDpress, 2017. https://tud.qucosa.de/id/qucosa%3A30888.
Full textKHAN, SULTAN DAUD. "Automatic Detection and Computer Vision Analysis of Flow Dynamics and Social Groups in Pedestrian Crowds." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2016. http://hdl.handle.net/10281/102644.
Full textJan, Yasir. "Novel architectures for spectator crowd image analysis." Thesis, Jan, Yasir (2020) Novel architectures for spectator crowd image analysis. PhD thesis, Murdoch University, 2020. https://researchrepository.murdoch.edu.au/id/eprint/59147/.
Full textGuler, Puren. "Automated Crowd Behavior Analysis For Video Surveillance Applications." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614659/index.pdf.
Full textpeople counting, people tracking and crowd behavior analysis. In this thesis, the behavior understanding will be used for crowd behavior analysis. In the literature, there are two types of approaches for behavior understanding problem: analyzing behaviors of individuals in a crowd (object based) and using this knowledge to make deductions regarding the crowd behavior and analyzing the crowd as a whole (holistic based). In this work, a holistic approach is used to develop a real-time abnormality detection in crowds using scale invariant feature transform (SIFT) based features and unsupervised machine learning techniques.
Bisagno, Niccolò. "On simulating and predicting pedestrian trajectories in a crowd." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/256722.
Full textUllah, Habib. "Crowd Motion Analysis: Segmentation, Anomaly Detection, and Behavior Classification." Doctoral thesis, Università degli studi di Trento, 2015. https://hdl.handle.net/11572/369001.
Full textFagette, Antoine. "Détection de foule et analyse de comportement par analyse vidéo." Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066709.
Full textThis thesis focuses on the similarity between a fluid and a crowd and on the adaptation of the particle video algorithm for crowd tracking and analysis. This interrogation ended up with the design of a complete system for crowd analysis out of which, this thesis has addressed three main problems: the detection of the crowd, the estimation of its density and the tracking of the flow in order to derive some behavior features.The contribution to crowd detection introduces a totally unsupervised method for the detection and location of dense crowds in images without context-awareness. After retrieving multi-scale texture-related feature vectors from the image, a binary classification is conducted to identify the crowd and the background.The density estimation algorithm is tackling the problem of learning regression models when it comes to large dense crowds. In such cases, the learning is impossible on real data as the ground truth is not available. Our method relies on the use of synthetic data for the learning phase and proves that the regression model obtained is valid for a use on real data.Our adaptation of the particle video algorithm leads us to consider the cloud of particles as statistically representative of the crowd. Therefore, each particle has physical properties that enable us to assess the validity of its behavior according to the one expected from a pedestrian, and to optimize its motion guided by the optical flow. This leads us to three applications: the detection of the entry and exit areas of the crowd in the image, the detection of dynamic occlusions and the possibility to link entry areas with exit ones, according to the flow of the pedestrians
Books on the topic "Crowd Analysi"
Ali, Saad, Ko Nishino, Dinesh Manocha, and Mubarak Shah, eds. Modeling, Simulation and Visual Analysis of Crowds. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8483-7.
Full textN, Pathak P., and Bhabha Atomic Research Centre, eds. Extraction chromatographic studies on a strontium selective crown ether. Mumbai: Bhabha Atomic Research Centre, 1998.
Find full textAssociates, Golder, and Canada Centre for Mineral and Energy Technology., eds. Crown pillar stability back-analysis: Report to CANMET. Mississauga, Ont: Golder Associates Ltd., 1990.
Find full textSunkin, Maurice. The nature of the crown: A legal and political analysis. Oxford: Oxford University Press, 1999.
Find full textTonasket Ranger District (Wash.), Washington (State). Dept. of Ecology., and TerraMatrix Inc, eds. Crown Jewel Mine, draft environmental impact statement. Steamboat Springs, CO: TerraMatrix, 1995.
Find full textPlummer, Tony. The psychology of technical analysis: Profiting from crowd behavior and the dynamics of price. Chicago: Probus Pub. Co., 1993.
Find full textCrow-Omaha: New light on a classic problem of kinship analysis. Tucson: University of Arizona Press, 2012.
Find full textOntario. Ministry of Natural Resources. An environmental assessment of timber management on crown lands in the Megisan Lake area. Toronto: The Committee, 1996.
Find full textSentiment in the Forex market: Indicators and strategies to profit from crowd behavior and market extremes. Hoboken, N.J: John Wiley & Sons, 2008.
Find full textCerrah, Ibrahim. Crowds and public order policing: An analysis of crowds and interpretations of their behaviour based on observational studies in Turkey, England, and Wales. Aldershot: Ashgate/Dartmouth, 1998.
Find full textBook chapters on the topic "Crowd Analysi"
Still, G. Keith. "RAMP analysis." In Applied Crowd Science, 103–17. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781351053068-5.
Full textStill, G. Keith. "Event egress analysis." In Applied Crowd Science, 159–67. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781351053068-10.
Full textStill, G. Keith. "Crowd risk analysis." In Applied Crowd Science, 149–58. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781351053068-9.
Full textStill, G. Keith. "Strategic and tactical analysis." In Applied Crowd Science, 169–81. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781351053068-11.
Full textAmsterdamer, Yael, and Tova Milo. "Crowd Mining and Analysis." In Encyclopedia of Database Systems, 1–4. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4899-7993-3_80657-2.
Full textAmsterdamer, Yael, and Tova Milo. "Crowd Mining and Analysis." In Encyclopedia of Database Systems, 698–701. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_80657.
Full textRyan, David, Simon Denman, Sridha Sridharan, and Clinton Fookes. "Scene Invariant Crowd Counting and Crowd Occupancy Analysis." In Studies in Computational Intelligence, 161–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28598-1_6.
Full textFeliciani, Claudio, Kenichiro Shimura, and Katsuhiro Nishinari. "Analysis of Past Crowd Accidents." In Introduction to Crowd Management, 51–73. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-90012-0_3.
Full textWąs, Jarosław, and Krzysztof Kułakowski. "Social Groups in Crowd." In Encyclopedia of Social Network Analysis and Mining, 1–7. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4614-7163-9_255-1.
Full textWąs, Jarosław, and Krzysztof Kułakowski. "Social Groups in Crowd." In Encyclopedia of Social Network Analysis and Mining, 1784–90. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-6170-8_255.
Full textConference papers on the topic "Crowd Analysi"
De Luca, Antonio, Scott Lomax, and Marguerite Jeansonne Pinto. "Advanced analysis of a pedestrian bridge and considerations on crowd-structure interaction." In IABSE Symposium, Prague 2022: Challenges for Existing and Oncoming Structures. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2022. http://dx.doi.org/10.2749/prague.2022.1427.
Full textDeshpande, N. P., and R. Gupta. "Crowd management using fuzzy logic and G.I.S." In RISK ANALYSIS 2010. Southampton, UK: WIT Press, 2010. http://dx.doi.org/10.2495/risk100281.
Full textHuang, Hun, Ge Gao, Ziyi Ke, Cheng Peng, and Ming Gu. "A Multi-Scenario Crowd Data Synthesis Based On Building Information Modeling." In The 29th EG-ICE International Workshop on Intelligent Computing in Engineering. EG-ICE, 2022. http://dx.doi.org/10.7146/aul.455.c223.
Full textMahata, Debanjan, and Nitin Agarwal. "Learning from the crowd." In ASONAM '13: Advances in Social Networks Analysis and Mining 2013. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2492517.2492661.
Full textZubrilina, E. M., V. I. Novikov, H. S. Jamalov, and V. S. Kompaniets. "ANALYSIS OF CROWDSOURCING INTERNET PLATFORMS AND THEIR IMPLEMENTATION IN THE EDUCATIONAL ENVIRONMENT." In STATE AND DEVELOPMENT PROSPECTS OF AGRIBUSINESS Volume 2. DSTU-Print, 2020. http://dx.doi.org/10.23947/interagro.2020.2.588-590.
Full textStuart, Daniel, Keith Christensen, Anthony Chen, Yong Kim, and YangQuan Chen. "Utilizing Augmented Reality Technology for Crowd Pedestrian Analysis Involving Individuals With Disabilities." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12765.
Full textCao, Tian, Xinyu Wu, Jinnian Guo, Shiqi Yu, and Yangsheng Xu. "Abnormal crowd motion analysis." In 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE, 2009. http://dx.doi.org/10.1109/robio.2009.5420408.
Full textDuyar, Mustafa. "Mass Conserving Elastohydrodynamic Piston Lubrication Model With Incorporated Crown Lands." In ASME 2007 Internal Combustion Engine Division Fall Technical Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/icef2007-1710.
Full textDupont, Camille, Luis Tobias, and Bertrand Luvison. "Crowd-11: A Dataset for Fine Grained Crowd Behaviour Analysis." In 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, 2017. http://dx.doi.org/10.1109/cvprw.2017.271.
Full textPhu, Quy Nguyen Pham, Vy Nguyen, Tien Do, and Thanh Duc Ngo. "Measuring Crowd Collectiveness with Trajectory Smoothing." In 2018 1st International Conference on Multimedia Analysis and Pattern Recognition (MAPR). IEEE, 2018. http://dx.doi.org/10.1109/mapr.2018.8337520.
Full textReports on the topic "Crowd Analysi"
Petty, Mikel D., Ryland C. Gaskins, and Frederic D. McKenzie. Crowd Modeling in Military Simulations: Requirements Analysis, Survey, and Design Study. Fort Belvoir, VA: Defense Technical Information Center, April 2003. http://dx.doi.org/10.21236/ada474641.
Full textSchomaker, Michael E., Stanley J. Zarnoch, William A. Bechtold, David J. Latelle, William G. Burkman, and Susan M. Cox. Crown-condition classification: a guide to data collection and analysis. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station, 2007. http://dx.doi.org/10.2737/srs-gtr-102.
Full textDrury, J., S. Arias, T. Au-Yeung, D. Barr, L. Bell, T. Butler, H. Carter, et al. Public behaviour in response to perceived hostile threats: an evidence base and guide for practitioners and policymakers. University of Sussex, 2023. http://dx.doi.org/10.20919/vjvt7448.
Full textAnilkumar, Rahul, Benjamin Melone, Michael Patsula, Christopher Tran, Christopher Wang, Kevin Dick, Hoda Khalil, and G. A. Wainer. Canadian jobs amid a pandemic : examining the relationship between professional industry and salary to regional key performance indicators. Department of Systems and Computer Engineering, Carleton University, June 2022. http://dx.doi.org/10.22215/dsce/220608.
Full textRandolph, KaDonna C. Descriptive statistics of tree crown condition in the Southern United States and impacts on data analysis and interpretation. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station, 2006. http://dx.doi.org/10.2737/srs-gtr-94.
Full textRandolph, KaDonna C. Descriptive statistics of tree crown condition in the Southern United States and impacts on data analysis and interpretation. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station, 2006. http://dx.doi.org/10.2737/srs-gtr-94.
Full textChen, Li, Yu Ji, QiPeng Wang, and Peng Chen. Effects of traditional Chinese exercise on the treatment of COVID-19: a protocol for a systematic review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, January 2022. http://dx.doi.org/10.37766/inplasy2022.1.0089.
Full textArce, Eliécer, and Edgar A. Robles. Fiscal Rules and the Behavior of Public Investment in Costa Rica and Panama: Towards Growth-Friendly Fiscal Policy? Inter-American Development Bank, March 2021. http://dx.doi.org/10.18235/0003071.
Full textLu, Tianjun, Jian-yu Ke, Fynnwin Prager, and Jose N. Martinez. “TELE-commuting” During the COVID-19 Pandemic and Beyond: Unveiling State-wide Patterns and Trends of Telecommuting in Relation to Transportation, Employment, Land Use, and Emissions in Calif. Mineta Transportation Institute, August 2022. http://dx.doi.org/10.31979/mti.2022.2147.
Full textRon, Eliora, and Eugene Eugene Nester. Global functional genomics of plant cell transformation by agrobacterium. United States Department of Agriculture, March 2009. http://dx.doi.org/10.32747/2009.7695860.bard.
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