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Artykuły w czasopismach na temat "Videos analytics"
Jain, Puneet, Justin Manweiler, Arup Acharya i Romit Roy Choudhury. "Scalable Social Analytics for Live Viral Event Prediction". Proceedings of the International AAAI Conference on Web and Social Media 8, nr 1 (16.05.2014): 226–35. http://dx.doi.org/10.1609/icwsm.v8i1.14504.
Pełny tekst źródłaArulraj, Joy. "Accelerating Video Analytics". ACM SIGMOD Record 50, nr 4 (31.01.2022): 39–40. http://dx.doi.org/10.1145/3516431.3516442.
Pełny tekst źródłaWang, Han, Shangyu Xie i Yuan Hong. "VideoDP: A Flexible Platform for Video Analytics with Differential Privacy". Proceedings on Privacy Enhancing Technologies 2020, nr 4 (1.10.2020): 277–96. http://dx.doi.org/10.2478/popets-2020-0073.
Pełny tekst źródłaDolores, Maria, i Jorge Mañana-Rodriguez. "Exploring Engagement in Online Videos for Language Learning through YouTube’s Learning Analytics". EDEN Conference Proceedings, nr 1 (21.09.2021): 49–58. http://dx.doi.org/10.38069/edenconf-2021-ac0005.
Pełny tekst źródłaZhang, Jingjing, Yicheng Huang i Ming Gao. "Video Features, Engagement, and Patterns of Collective Attention Allocation". Journal of Learning Analytics 9, nr 1 (11.03.2022): 32–52. http://dx.doi.org/10.18608/jla.2022.7421.
Pełny tekst źródłaCarpenter, Chris. "Computer Vision Analytics Enables Determination of Rig State". Journal of Petroleum Technology 74, nr 01 (1.01.2022): 96–98. http://dx.doi.org/10.2118/0122-0096-jpt.
Pełny tekst źródłaLiu, Ying, Dickson K. W. Chiu i Kevin K. W. Ho. "Short-Form Videos for Public Library Marketing: Performance Analytics of Douyin in China". Applied Sciences 13, nr 6 (7.03.2023): 3386. http://dx.doi.org/10.3390/app13063386.
Pełny tekst źródłaLuo, Zhiming, Pierre-Marc Jodoin, Song-Zhi Su, Shao-Zi Li i Hugo Larochelle. "Traffic Analytics With Low-Frame-Rate Videos". IEEE Transactions on Circuits and Systems for Video Technology 28, nr 4 (kwiecień 2018): 878–91. http://dx.doi.org/10.1109/tcsvt.2016.2632439.
Pełny tekst źródłaDAUN, Felipe, i Ana Maria Dianezi GAMBARDELLA. "Educational videos with nutritional approach in YouTube". Revista de Nutrição 31, nr 3 (maj 2018): 339–49. http://dx.doi.org/10.1590/1678-98652018000300007.
Pełny tekst źródłaXiao, Sihan. "More than Data: A Multivocal Inquiry into Video-Based Research on Learning and Teaching". ECNU Review of Education 1, nr 3 (wrzesień 2018): 23–35. http://dx.doi.org/10.30926/ecnuroe2018010302.
Pełny tekst źródłaRozprawy doktorskie na temat "Videos analytics"
Abdallah, Raed. "Intelligent crime detection and behavioral pattern mining : a comprehensive study". Electronic Thesis or Diss., Université Paris Cité, 2023. http://www.theses.fr/2023UNIP7031.
Pełny tekst źródłaIn the face of a rapidly evolving criminal landscape, law enforcement agencies (LEAs) grapple with escalating challenges in contemporary criminal investigations. This PhD thesis embarks on a transformative exploration, encouraged by an urgent need to revolutionize investigative methodologies and arm LEAs with state-of-the-art tools to combat crime effectively. Rooted in this imperative motivation, the research meticulously navigates diverse data sources, including the intricate web of social media networks, omnipresent video surveillance systems, and expansive online platforms, recognizing their fundamental roles in modern crime detection. The contextual backdrop of this research is the pressing demand to empower LEAs with advanced capabilities in intelligent crime detection. The surge in digital interactions necessitates a paradigm shift, compelling researchers to delve deep into the labyrinth of social media, surveillance footage, and online data. This context underscores the urgency to fortify law enforcement strategies with cutting-edge technological solutions. Motivated by urgency, the thesis focuses on three core objectives: firstly, automating suspect identification through the integration of data science, big data tools, and ontological models, streamlining investigations and empowering law enforcement with advanced inference rules; secondly, enabling real-time detection of criminal events within digital noise via intricate ontological models and advanced inference rules, providing actionable intelligence and supporting informed decision-making for law enforcement; and thirdly, enhancing video surveillance by integrating advanced deep learning algorithms for swift and precise detection of knife-related crimes, representing a pioneering advancement in video surveillance technology. Navigating this research terrain poses significant challenges. The integration of heterogeneous data demands robust preprocessing techniques, enabling the harmonious fusion of disparate data types. Real-time analysis of social media intricacies necessitates ontological models adept at discerning subtle criminal nuances within the digital tapestry. Moreover, designing Smart Video Surveillance Systems necessitates the fusion of state-of-the-art deep learning algorithms with real-time video processing, ensuring both speed and precision in crime detection. Against these challenges, the thesis contributes innovative solutions at the forefront of contemporary crime detection technology. The research introduces ICAD, an advanced framework automating suspect identification and revolutionizing investigations. CRI-MEDIA tackles social media crime challenges using a streamlined process and enriched criminal ontology. Additionally, SVSS, a Smart Video Surveillance System, swiftly detects knife-related crimes, enhancing public safety. Integrating ICAD, CRI-MEDIA, and SVSS, this work pioneers intelligent crime detection, empowering law enforcement with unprecedented capabilities in the digital age. Critical to the integrity of the research, the proposed methodologies undergo rigorous experimentation in authentic criminal scenarios. Real-world data gathered from actual investigations form the crucible wherein ICAD, CRI-MEDIA, and SVSS are tested. These experiments serve as a litmus test, affirming not only the viability of the proposed solutions but also offering nuanced insights for further refinement. The results underscore the practical applicability of these methodologies, their adaptability in diverse law enforcement contexts, and their role in enhancing public safety and security
Carpani, Valerio. "CNN-based video analytics". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018.
Znajdź pełny tekst źródłaPettersson, Johan, i Robin Veteläinen. "A comparison of solutions to measure Quality of Service for video streams". Thesis, KTH, Data- och elektroteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-188514.
Pełny tekst źródłaDet finns fler och fler personer som tittar på video strömmar på Internet, detta har lett till att nya företag har startats som konkurerar om tittare. För att förbättra kundupplevelsen kan man mäta hur tjänsten presterar. Målet med examensarbetet var att rekommendera hur man kan mäta tjänstekvalite för en realtidsvideoströmningstjänst. Tre olika lösningsförslag presenterades; att köpa informationen från en content delivery network, att bygga vidare på tillgängliga analytisk mjukvara eller att bygga ett eget paketsniffarprogram. Det bestämdes att bygga vidare på tillgänglig analytisk mjukvara. Fyra olika mjukvara jämfördes: Google Analytics, Mixpanel, Ooyala IQ och Piwik. Jämförelsen gjordes med hjälp av analytical hierarchy process, de olika alternativen jämfördes med avseende på: hur moget API:et var, flexibilitet, visualiseringen av data och support. Rekommendationen är att använda sig av Ooyala IQ som utmärker sig med avseende på flexibilitet, det var enkelt att använda deras API i sin egen lösning, det fanns ingen gräns på hur många händelser man kunde lagra per månad, och slutligen så fanns det dedikerad supportpersonal att nå via telefon eller email.
Hassan, Waqas. "Video analytics for security systems". Thesis, University of Sussex, 2013. http://sro.sussex.ac.uk/id/eprint/43406/.
Pełny tekst źródłaAsif, Muhammad. "Video analytics for intelligent surveillance systems". Thesis, University of Strathclyde, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.530322.
Pełny tekst źródłaHöferlin, Benjamin [Verfasser]. "Scalable Visual Analytics for Video Surveillance / Benjamin Höferlin". München : Verlag Dr. Hut, 2014. http://d-nb.info/1050331842/34.
Pełny tekst źródłaCheng, Guangchun. "Video Analytics with Spatio-Temporal Characteristics of Activities". Thesis, University of North Texas, 2015. https://digital.library.unt.edu/ark:/67531/metadc799541/.
Pełny tekst źródłaLuo, Ning. "A Wireless Traffic Surveillance System Using Video Analytics". Thesis, University of North Texas, 2011. https://digital.library.unt.edu/ark:/67531/metadc68005/.
Pełny tekst źródłaBarracu, Maria Antonietta. "Tecniche, metodologie e strumenti per la Web Analytics, con particolare attenzione sulla Video Analytics". Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2011. http://amslaurea.unibo.it/1919/.
Pełny tekst źródłaHöferlin, Markus Johannes [Verfasser], i Daniel [Akademischer Betreuer] Weiskopf. "Video visual analytics / Markus Johannes Höferlin. Betreuer: Daniel Weiskopf". Stuttgart : Universitätsbibliothek der Universität Stuttgart, 2013. http://d-nb.info/1037955935/34.
Pełny tekst źródłaKsiążki na temat "Videos analytics"
Distante, Cosimo, Sebastiano Battiato i Andrea Cavallaro, red. Video Analytics for Audience Measurement. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12811-5.
Pełny tekst źródłaShan, Caifeng, Fatih Porikli, Tao Xiang i Shaogang Gong, red. Video Analytics for Business Intelligence. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28598-1.
Pełny tekst źródłaShan, Caifeng. Video Analytics for Business Intelligence. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Znajdź pełny tekst źródłaEl-Alfy, El-Sayed M., George Bebis i Mengchu Zhou. Intelligent Image and Video Analytics. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003053262.
Pełny tekst źródłaBai, Xiang, Yi Fang, Yangqing Jia, Meina Kan, Shiguang Shan, Chunhua Shen, Jingdong Wang i in., red. Video Analytics. Face and Facial Expression Recognition. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12177-8.
Pełny tekst źródłaNasrollahi, Kamal, Cosimo Distante, Gang Hua, Andrea Cavallaro, Thomas B. Moeslund, Sebastiano Battiato i Qiang Ji, red. Video Analytics. Face and Facial Expression Recognition and Audience Measurement. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56687-0.
Pełny tekst źródła1953-, Okuda Ted, red. The Jerry Lewis films: An analytical filmography of the innovative comic. Jefferson, N.C: McFarland, 1995.
Znajdź pełny tekst źródłaAnzinger, Martina. Gainborough pictures reframed, or, Raising Jane Austen for 1990s film: A film-historic and film-analytical study for the 1955 films Sense and sensibility and Persuasion. Frankfurt am Main: P. Lang, 2003.
Znajdź pełny tekst źródłaXiang, Tao, Caifeng Shan i Fatih Porikli. Video Analytics for Business Intelligence. Springer, 2012.
Znajdź pełny tekst źródłaVideo Analytics For Business Intelligence. Springer, 2012.
Znajdź pełny tekst źródłaCzęści książek na temat "Videos analytics"
Dhanwal, Swapnil, Vishnu Bhaskar i Tanya Agarwal. "Automated Censoring of Cigarettes in Videos Using Deep Learning Techniques". W Asset Analytics, 339–48. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3643-4_26.
Pełny tekst źródłaGuru, D. S., V. K. Jyothi i Y. H. Sharath Kumar. "Features Fusion for Retrieval of Flower Videos". W Data Analytics and Learning, 221–33. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2514-4_19.
Pełny tekst źródłaAgrawal, Swati, i Ashish Sureka. "Copyright Infringement Detection of Music Videos on YouTube by Mining Video and Uploader Meta-data". W Big Data Analytics, 48–67. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-03689-2_4.
Pełny tekst źródłaManohar, N., Y. H. Sharath Kumar, G. Hemantha Kumar i Radhika Rani. "Deep Learning Approach for Classification of Animal Videos". W Data Analytics and Learning, 421–31. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2514-4_35.
Pełny tekst źródłaBaluch, Farhan, i Laurent Itti. "Mining Videos for Features that Drive Attention". W Multimedia Data Mining and Analytics, 311–26. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14998-1_14.
Pełny tekst źródłaSingh, Neha, Onkareshwar Prasad i T. Sujithra. "Deep Learning-Based Violence Detection from Videos". W Intelligent Data Engineering and Analytics, 323–32. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6624-7_32.
Pełny tekst źródłaSunny, Alfina, i N. Manohar. "Detection, Classification and Counting of Moving Vehicles from Videos". W Data Analytics and Learning, 231–42. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-6346-1_19.
Pełny tekst źródłaDing, Lei, i Alper Yilmaz. "Learning Social Relations from Videos: Features, Models, and Analytics". W Human-Centered Social Media Analytics, 21–41. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05491-9_2.
Pełny tekst źródłaShaliyar, Mohd, i Khurram Mustafa. "Source Authentication of Videos Shared on Social Media". W Intelligent Data Analytics, IoT, and Blockchain, 102–13. Boca Raton: Auerbach Publications, 2023. http://dx.doi.org/10.1201/9781003371380-10.
Pełny tekst źródłaVenkatraman, Santhi, i Puja Saha. "Multimodal Architecture for Emotion Prediction in Videos Using Ensemble Learning". W Big Data Analytics in Smart Manufacturing, 109–20. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003202776-6.
Pełny tekst źródłaStreszczenia konferencji na temat "Videos analytics"
Chatar, Crispin, Suhas Suresha, Laetitia Shao, Soumya Gupta i Indranil Roychoudhury. "Determining Rig State from Computer Vision Analytics". W SPE/IADC International Drilling Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/204086-ms.
Pełny tekst źródłaLy, Anna, Tingting Zhu i Andrew Petersen. "Evaluating Storytelling Videos Using YouTube Analytics". W SIGCSE 2024: The 55th ACM Technical Symposium on Computer Science Education. New York, NY, USA: ACM, 2024. http://dx.doi.org/10.1145/3626253.3635503.
Pełny tekst źródłaQingbo Hu, Guan Wang i Philip S. Yu. "Assessing the longevity of online videos: A new insight of a video's quality". W 2014 International Conference on Data Science and Advanced Analytics (DSAA). IEEE, 2014. http://dx.doi.org/10.1109/dsaa.2014.7058044.
Pełny tekst źródłaZhang, Yi, Fan Luan i Yu-Gang Jiang. "Smart Advertising in Videos Based on Comprehensive Content Analytics". W 2019 IEEE International Conference on Multimedia & Expo Workshops (ICMEW). IEEE, 2019. http://dx.doi.org/10.1109/icmew.2019.00113.
Pełny tekst źródłaTsai, Min-Han, Nalini Venkatasubramanian i Cheng-Hsin Hsu. "Analytics-Aware Storage of Surveillance Videos: Implementation and Optimization". W 2020 IEEE International Conference on Smart Computing (SMARTCOMP). IEEE, 2020. http://dx.doi.org/10.1109/smartcomp50058.2020.00024.
Pełny tekst źródłaBarnes, Stuart J., i Weisha Wang. "Understanding Consumer Advertising via Audio Analytics of Sports Videos". W 2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC). IEEE, 2023. http://dx.doi.org/10.1109/icaiic57133.2023.10067125.
Pełny tekst źródłaKadoic, Nikola, i Dijana Oreski. "Learning Analytics of YouTube Videos Linked to LMS Moodle". W 2021 44th International Convention on Information, Communication and Electronic Technology (MIPRO). IEEE, 2021. http://dx.doi.org/10.23919/mipro52101.2021.9597168.
Pełny tekst źródłaSaquib, Nazmus, Faria Huq i Syed Arefinul Haque. "graphiti: Sketch-based Graph Analytics for Images and Videos". W CHI '22: CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3491102.3501923.
Pełny tekst źródłaMomeni, Hamed, i Arvin Ebrahimkhanlou. "Applications of High-Dimensional Data Analytics in Structural Health Monitoring and Non-Destructive Evaluation: Thermal Videos Processing Using Tensor-Based Analysis". W ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-71878.
Pełny tekst źródłaM.R., Anala, Malika Makker i Aakanksha Ashok. "Anomaly Detection in Surveillance Videos". W 2019 26th International Conference on High Performance Computing, Data and Analytics Workshop (HiPCW). IEEE, 2019. http://dx.doi.org/10.1109/hipcw.2019.00031.
Pełny tekst źródłaRaporty organizacyjne na temat "Videos analytics"
Simpson, Diane, Michelle Brennan i Susan Gomperts. Strategic roadmap for interoperable public safety video analytics. Gaithersburg, MD: National Institute of Standards and Technology, marzec 2020. http://dx.doi.org/10.6028/nist.ir.8299.
Pełny tekst źródłaSimpson, Diane, Michelle Brennan i Susan Gomperts. Strategic roadmap for interoperable public safety video analytics. Gaithersburg, MD: National Institute of Standards and Technology, kwiecień 2020. http://dx.doi.org/10.6028/nist.sp.1500-15.
Pełny tekst źródłaGuan, Haiying, Daniel Zhou, Jonathan Fiscus, John Garofolo i James Horan. Evaluation infrastructure for the measurement of content-based video quality and video analytics performance. Gaithersburg, MD: National Institute of Standards and Technology, lipiec 2017. http://dx.doi.org/10.6028/nist.ir.8187.
Pełny tekst źródłaRussell, John. Deliberate Motion Analytics Fused Radar and Video Test Results Deployed Beyond the Perimeter Fence in a High Noise Environment. Office of Scientific and Technical Information (OSTI), maj 2021. http://dx.doi.org/10.2172/1855028.
Pełny tekst źródłaAguilar, G., H. Waqa-Sakiti i L. Winder. Using Predicted Locations and an Ensemble Approach to Address Sparse Data Sets for Species Distribution Modelling: Long-horned Beetles (Cerambycidae) of the Fiji Islands. Unitec ePress, grudzień 2016. http://dx.doi.org/10.34074/book.008.
Pełny tekst źródłaPokryshen, Dmytro A., Evgeniy H. Prokofiev i Albert A. Azaryan. Blogger and YouTube services at a distant course “Database management system Microsoft Access”. [б. в.], wrzesień 2019. http://dx.doi.org/10.31812/123456789/3272.
Pełny tekst źródłaYatsymirska, Mariya. MODERN MEDIA TEXT: POLITICAL NARRATIVES, MEANINGS AND SENSES, EMOTIONAL MARKERS. Ivan Franko National University of Lviv, luty 2022. http://dx.doi.org/10.30970/vjo.2022.51.11411.
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