Auswahl der wissenschaftlichen Literatur zum Thema „Videos analytics“
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Zeitschriftenartikel zum Thema "Videos analytics"
Jain, Puneet, Justin Manweiler, Arup Acharya und 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.
Der volle Inhalt der QuelleArulraj, Joy. „Accelerating Video Analytics“. ACM SIGMOD Record 50, Nr. 4 (31.01.2022): 39–40. http://dx.doi.org/10.1145/3516431.3516442.
Der volle Inhalt der QuelleWang, Han, Shangyu Xie und Yuan Hong. „VideoDP: A Flexible Platform for Video Analytics with Differential Privacy“. Proceedings on Privacy Enhancing Technologies 2020, Nr. 4 (01.10.2020): 277–96. http://dx.doi.org/10.2478/popets-2020-0073.
Der volle Inhalt der QuelleDolores, Maria, und 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.
Der volle Inhalt der QuelleZhang, Jingjing, Yicheng Huang und 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.
Der volle Inhalt der QuelleCarpenter, Chris. „Computer Vision Analytics Enables Determination of Rig State“. Journal of Petroleum Technology 74, Nr. 01 (01.01.2022): 96–98. http://dx.doi.org/10.2118/0122-0096-jpt.
Der volle Inhalt der QuelleLiu, Ying, Dickson K. W. Chiu und Kevin K. W. Ho. „Short-Form Videos for Public Library Marketing: Performance Analytics of Douyin in China“. Applied Sciences 13, Nr. 6 (07.03.2023): 3386. http://dx.doi.org/10.3390/app13063386.
Der volle Inhalt der QuelleLuo, Zhiming, Pierre-Marc Jodoin, Song-Zhi Su, Shao-Zi Li und Hugo Larochelle. „Traffic Analytics With Low-Frame-Rate Videos“. IEEE Transactions on Circuits and Systems for Video Technology 28, Nr. 4 (April 2018): 878–91. http://dx.doi.org/10.1109/tcsvt.2016.2632439.
Der volle Inhalt der QuelleDAUN, Felipe, und Ana Maria Dianezi GAMBARDELLA. „Educational videos with nutritional approach in YouTube“. Revista de Nutrição 31, Nr. 3 (Mai 2018): 339–49. http://dx.doi.org/10.1590/1678-98652018000300007.
Der volle Inhalt der QuelleXiao, Sihan. „More than Data: A Multivocal Inquiry into Video-Based Research on Learning and Teaching“. ECNU Review of Education 1, Nr. 3 (September 2018): 23–35. http://dx.doi.org/10.30926/ecnuroe2018010302.
Der volle Inhalt der QuelleDissertationen zum Thema "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.
Der volle Inhalt der QuelleIn 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.
Den vollen Inhalt der Quelle findenPettersson, Johan, und 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.
Der volle Inhalt der QuelleDet 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/.
Der volle Inhalt der QuelleAsif, Muhammad. „Video analytics for intelligent surveillance systems“. Thesis, University of Strathclyde, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.530322.
Der volle Inhalt der QuelleHöferlin, Benjamin [Verfasser]. „Scalable Visual Analytics for Video Surveillance / Benjamin Höferlin“. München : Verlag Dr. Hut, 2014. http://d-nb.info/1050331842/34.
Der volle Inhalt der QuelleCheng, Guangchun. „Video Analytics with Spatio-Temporal Characteristics of Activities“. Thesis, University of North Texas, 2015. https://digital.library.unt.edu/ark:/67531/metadc799541/.
Der volle Inhalt der QuelleLuo, Ning. „A Wireless Traffic Surveillance System Using Video Analytics“. Thesis, University of North Texas, 2011. https://digital.library.unt.edu/ark:/67531/metadc68005/.
Der volle Inhalt der QuelleBarracu, 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/.
Der volle Inhalt der QuelleHöferlin, Markus Johannes [Verfasser], und 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.
Der volle Inhalt der QuelleBücher zum Thema "Videos analytics"
Distante, Cosimo, Sebastiano Battiato und Andrea Cavallaro, Hrsg. Video Analytics for Audience Measurement. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12811-5.
Der volle Inhalt der QuelleShan, Caifeng, Fatih Porikli, Tao Xiang und Shaogang Gong, Hrsg. Video Analytics for Business Intelligence. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28598-1.
Der volle Inhalt der QuelleShan, Caifeng. Video Analytics for Business Intelligence. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Den vollen Inhalt der Quelle findenEl-Alfy, El-Sayed M., George Bebis und Mengchu Zhou. Intelligent Image and Video Analytics. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003053262.
Der volle Inhalt der QuelleBai, Xiang, Yi Fang, Yangqing Jia, Meina Kan, Shiguang Shan, Chunhua Shen, Jingdong Wang et al., Hrsg. Video Analytics. Face and Facial Expression Recognition. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12177-8.
Der volle Inhalt der QuelleNasrollahi, Kamal, Cosimo Distante, Gang Hua, Andrea Cavallaro, Thomas B. Moeslund, Sebastiano Battiato und Qiang Ji, Hrsg. 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.
Der volle Inhalt der Quelle1953-, Okuda Ted, Hrsg. The Jerry Lewis films: An analytical filmography of the innovative comic. Jefferson, N.C: McFarland, 1995.
Den vollen Inhalt der Quelle findenAnzinger, 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.
Den vollen Inhalt der Quelle findenXiang, Tao, Caifeng Shan und Fatih Porikli. Video Analytics for Business Intelligence. Springer, 2012.
Den vollen Inhalt der Quelle findenVideo Analytics For Business Intelligence. Springer, 2012.
Den vollen Inhalt der Quelle findenBuchteile zum Thema "Videos analytics"
Dhanwal, Swapnil, Vishnu Bhaskar und Tanya Agarwal. „Automated Censoring of Cigarettes in Videos Using Deep Learning Techniques“. In Asset Analytics, 339–48. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3643-4_26.
Der volle Inhalt der QuelleGuru, D. S., V. K. Jyothi und Y. H. Sharath Kumar. „Features Fusion for Retrieval of Flower Videos“. In Data Analytics and Learning, 221–33. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2514-4_19.
Der volle Inhalt der QuelleAgrawal, Swati, und Ashish Sureka. „Copyright Infringement Detection of Music Videos on YouTube by Mining Video and Uploader Meta-data“. In Big Data Analytics, 48–67. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-03689-2_4.
Der volle Inhalt der QuelleManohar, N., Y. H. Sharath Kumar, G. Hemantha Kumar und Radhika Rani. „Deep Learning Approach for Classification of Animal Videos“. In Data Analytics and Learning, 421–31. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2514-4_35.
Der volle Inhalt der QuelleBaluch, Farhan, und Laurent Itti. „Mining Videos for Features that Drive Attention“. In Multimedia Data Mining and Analytics, 311–26. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14998-1_14.
Der volle Inhalt der QuelleSingh, Neha, Onkareshwar Prasad und T. Sujithra. „Deep Learning-Based Violence Detection from Videos“. In Intelligent Data Engineering and Analytics, 323–32. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6624-7_32.
Der volle Inhalt der QuelleSunny, Alfina, und N. Manohar. „Detection, Classification and Counting of Moving Vehicles from Videos“. In Data Analytics and Learning, 231–42. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-6346-1_19.
Der volle Inhalt der QuelleDing, Lei, und Alper Yilmaz. „Learning Social Relations from Videos: Features, Models, and Analytics“. In Human-Centered Social Media Analytics, 21–41. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05491-9_2.
Der volle Inhalt der QuelleShaliyar, Mohd, und Khurram Mustafa. „Source Authentication of Videos Shared on Social Media“. In Intelligent Data Analytics, IoT, and Blockchain, 102–13. Boca Raton: Auerbach Publications, 2023. http://dx.doi.org/10.1201/9781003371380-10.
Der volle Inhalt der QuelleVenkatraman, Santhi, und Puja Saha. „Multimodal Architecture for Emotion Prediction in Videos Using Ensemble Learning“. In Big Data Analytics in Smart Manufacturing, 109–20. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003202776-6.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Videos analytics"
Chatar, Crispin, Suhas Suresha, Laetitia Shao, Soumya Gupta und Indranil Roychoudhury. „Determining Rig State from Computer Vision Analytics“. In SPE/IADC International Drilling Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/204086-ms.
Der volle Inhalt der QuelleLy, Anna, Tingting Zhu und Andrew Petersen. „Evaluating Storytelling Videos Using YouTube Analytics“. In 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.
Der volle Inhalt der QuelleQingbo Hu, Guan Wang und Philip S. Yu. „Assessing the longevity of online videos: A new insight of a video's quality“. In 2014 International Conference on Data Science and Advanced Analytics (DSAA). IEEE, 2014. http://dx.doi.org/10.1109/dsaa.2014.7058044.
Der volle Inhalt der QuelleZhang, Yi, Fan Luan und Yu-Gang Jiang. „Smart Advertising in Videos Based on Comprehensive Content Analytics“. In 2019 IEEE International Conference on Multimedia & Expo Workshops (ICMEW). IEEE, 2019. http://dx.doi.org/10.1109/icmew.2019.00113.
Der volle Inhalt der QuelleTsai, Min-Han, Nalini Venkatasubramanian und Cheng-Hsin Hsu. „Analytics-Aware Storage of Surveillance Videos: Implementation and Optimization“. In 2020 IEEE International Conference on Smart Computing (SMARTCOMP). IEEE, 2020. http://dx.doi.org/10.1109/smartcomp50058.2020.00024.
Der volle Inhalt der QuelleBarnes, Stuart J., und Weisha Wang. „Understanding Consumer Advertising via Audio Analytics of Sports Videos“. In 2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC). IEEE, 2023. http://dx.doi.org/10.1109/icaiic57133.2023.10067125.
Der volle Inhalt der QuelleKadoic, Nikola, und Dijana Oreski. „Learning Analytics of YouTube Videos Linked to LMS Moodle“. In 2021 44th International Convention on Information, Communication and Electronic Technology (MIPRO). IEEE, 2021. http://dx.doi.org/10.23919/mipro52101.2021.9597168.
Der volle Inhalt der QuelleSaquib, Nazmus, Faria Huq und Syed Arefinul Haque. „graphiti: Sketch-based Graph Analytics for Images and Videos“. In CHI '22: CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3491102.3501923.
Der volle Inhalt der QuelleMomeni, Hamed, und Arvin Ebrahimkhanlou. „Applications of High-Dimensional Data Analytics in Structural Health Monitoring and Non-Destructive Evaluation: Thermal Videos Processing Using Tensor-Based Analysis“. In ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-71878.
Der volle Inhalt der QuelleM.R., Anala, Malika Makker und Aakanksha Ashok. „Anomaly Detection in Surveillance Videos“. In 2019 26th International Conference on High Performance Computing, Data and Analytics Workshop (HiPCW). IEEE, 2019. http://dx.doi.org/10.1109/hipcw.2019.00031.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Videos analytics"
Simpson, Diane, Michelle Brennan und Susan Gomperts. Strategic roadmap for interoperable public safety video analytics. Gaithersburg, MD: National Institute of Standards and Technology, März 2020. http://dx.doi.org/10.6028/nist.ir.8299.
Der volle Inhalt der QuelleSimpson, Diane, Michelle Brennan und Susan Gomperts. Strategic roadmap for interoperable public safety video analytics. Gaithersburg, MD: National Institute of Standards and Technology, April 2020. http://dx.doi.org/10.6028/nist.sp.1500-15.
Der volle Inhalt der QuelleGuan, Haiying, Daniel Zhou, Jonathan Fiscus, John Garofolo und James Horan. Evaluation infrastructure for the measurement of content-based video quality and video analytics performance. Gaithersburg, MD: National Institute of Standards and Technology, Juli 2017. http://dx.doi.org/10.6028/nist.ir.8187.
Der volle Inhalt der QuelleRussell, 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), Mai 2021. http://dx.doi.org/10.2172/1855028.
Der volle Inhalt der QuelleAguilar, G., H. Waqa-Sakiti und 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, Dezember 2016. http://dx.doi.org/10.34074/book.008.
Der volle Inhalt der QuellePokryshen, Dmytro A., Evgeniy H. Prokofiev und Albert A. Azaryan. Blogger and YouTube services at a distant course “Database management system Microsoft Access”. [б. в.], September 2019. http://dx.doi.org/10.31812/123456789/3272.
Der volle Inhalt der QuelleYatsymirska, Mariya. MODERN MEDIA TEXT: POLITICAL NARRATIVES, MEANINGS AND SENSES, EMOTIONAL MARKERS. Ivan Franko National University of Lviv, Februar 2022. http://dx.doi.org/10.30970/vjo.2022.51.11411.
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