Auswahl der wissenschaftlichen Literatur zum Thema „Explicit content detection“
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Zeitschriftenartikel zum Thema "Explicit content detection"
Marcial Basilio, Jorge Alberto, Gualberto Aguilar Torres, Gabriel Sanchez Perez, Linda Karina Toscano Medina, Hector Manuel Perez Meana und Enrique Escamilla Hernadez. „Explicit Content Image Detection“. Signal & Image Processing : An International Journal 1, Nr. 2 (29.12.2010): 47–58. http://dx.doi.org/10.5121/sipij.2010.1205.
Der volle Inhalt der QuelleQamar Bhatti, Ali, Muhammad Umer, Syed Hasan Adil, Mansoor Ebrahim, Daniyal Nawaz und Faizan Ahmed. „Explicit Content Detection System: An Approach towards a Safe and Ethical Environment“. Applied Computational Intelligence and Soft Computing 2018 (04.07.2018): 1–13. http://dx.doi.org/10.1155/2018/1463546.
Der volle Inhalt der QuelleAppati, Justice Kwame, Kennedy Yaw Lodonu und Richmond Chris-Koka. „A Review of Image Analysis Techniques for Adult Content Detection“. International Journal of Software Innovation 9, Nr. 2 (April 2021): 102–21. http://dx.doi.org/10.4018/ijsi.2021040106.
Der volle Inhalt der QuelleChen, Xiaoyuan, Turki Aljrees, Muhammad Umer, Hanen Karamti, Saba Tahir, Nihal Abuzinadah, Khaled Alnowaiser, Ala’ Abdulmajid Eshmawi, Abdullah Mohamed und Imran Ashraf. „A novel approach for explicit song lyrics detection using machine and deep ensemble learning models“. PeerJ Computer Science 9 (30.08.2023): e1469. http://dx.doi.org/10.7717/peerj-cs.1469.
Der volle Inhalt der QuelleMuhammad Fadzli, Muhammad Arif Haikal, Mohd Fadzil Abu Hassan und Norazlin Ibrahim. „Explicit kissing scene detection in cartoon using convolutional long short-term memory“. Bulletin of Electrical Engineering and Informatics 11, Nr. 1 (01.02.2022): 213–20. http://dx.doi.org/10.11591/eei.v11i1.3542.
Der volle Inhalt der QuelleMarcial Basilio, Jorge A., Gualberto Aguilar Torres, Gabriel Sánchez Pérez, Karina Toscano Medina und Héctor M. Pérez Meana. „Novel method for pornographic image detection using HSV and YCbCr color models“. Revista Facultad de Ingeniería Universidad de Antioquia, Nr. 64 (03.10.2012): 79–90. http://dx.doi.org/10.17533/udea.redin.13117.
Der volle Inhalt der QuelleZhang, Linhao, Li Jin, Xian Sun, Guangluan Xu, Zequn Zhang, Xiaoyu Li, Nayu Liu, Qing Liu und Shiyao Yan. „TOT:Topology-Aware Optimal Transport for Multimodal Hate Detection“. Proceedings of the AAAI Conference on Artificial Intelligence 37, Nr. 4 (26.06.2023): 4884–92. http://dx.doi.org/10.1609/aaai.v37i4.25614.
Der volle Inhalt der QuelleBekaryan, Lilit. „Lost in “Transl-Hation”: Exploring the Impact of Machine Translation as an Intermediary Tool in Detecting Armenian Hate Speech“. Translation Studies: Theory and Practice 3, Nr. 2 (6) (25.12.2023): 40–47. http://dx.doi.org/10.46991/tstp/2023.3.2.040.
Der volle Inhalt der QuelleFOUCAMBERT, DENIS, und JACQUES BAILLÉ. „Evolution of the missing-letter effect among young readers between ages 5 and 8“. Applied Psycholinguistics 32, Nr. 1 (07.10.2010): 1–17. http://dx.doi.org/10.1017/s0142716410000263.
Der volle Inhalt der QuelleCela-Conde, Camilo J., Gisèle Marty, Enric Munar, Marcos Nadal und Lucrecia Burges. „The “Style Scheme” Grounds Perception of Paintings“. Perceptual and Motor Skills 95, Nr. 1 (August 2002): 91–100. http://dx.doi.org/10.2466/pms.2002.95.1.91.
Der volle Inhalt der QuelleDissertationen zum Thema "Explicit content detection"
Vaglio, Andrea. „Leveraging lyrics from audio for MIR“. Electronic Thesis or Diss., Institut polytechnique de Paris, 2021. http://www.theses.fr/2021IPPAT027.
Der volle Inhalt der QuelleLyrics provide a lot of information about music since they encapsulate a lot of the semantics of songs. Such information could help users navigate easily through a large collection of songs and to recommend new music to them. However, this information is often unavailable in its textual form. To get around this problem, singing voice recognition systems could be used to obtain transcripts directly from the audio. These approaches are generally adapted from the speech recognition ones. Speech transcription is a decades-old domain that has lately seen significant advancements due to developments in machine learning techniques. When applied to the singing voice, however, these algorithms provide poor results. For a number of reasons, the process of lyrics transcription remains difficult. In this thesis, we investigate several scientifically and industrially difficult ’Music Information Retrieval’ problems by utilizing lyrics information generated straight from audio. The emphasis is on making approaches as relevant in real-world settings as possible. This entails testing them on vast and diverse datasets and investigating their scalability. To do so, a huge publicly available annotated lyrics dataset is used, and several state-of-the-art lyrics recognition algorithms are successfully adapted. We notably present, for the first time, a system that detects explicit content directly from audio. The first research on the creation of a multilingual lyrics-toaudio system are as well described. The lyrics-toaudio alignment task is further studied in two experiments quantifying the perception of audio and lyrics synchronization. A novel phonotactic method for language identification is also presented. Finally, we provide the first cover song detection algorithm that makes explicit use of lyrics information extracted from audio
Buchteile zum Thema "Explicit content detection"
Vajda, Peter, Ivan Ivanov, Lutz Goldmann, Jong-Seok Lee und Touradj Ebrahimi. „Robust Duplicate Detection of 2D and 3D Objects“. In Methods and Innovations for Multimedia Database Content Management, 96–117. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-1791-9.ch007.
Der volle Inhalt der QuelleKhribi, Mohamed Koutheaïr, Mohamed Jemni und Olfa Nasraoui. „Automatic Personalization in E-Learning Based on Recommendation Systems“. In Intelligent and Adaptive Learning Systems, 19–33. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-60960-842-2.ch002.
Der volle Inhalt der QuelleWadhwani, Arun Kumar, Sulochana Wadhwani und Tripty Singh. „Computer Aided Diagnosis System for Breast Cancer Detection“. In Medical Imaging, 1002–19. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-0571-6.ch040.
Der volle Inhalt der QuelleWadhwani, Arun Kumar, Sulochana Wadhwani und Tripty Singh. „Computer Aided Diagnosis System for Breast Cancer Detection“. In Advances in Medical Technologies and Clinical Practice, 378–95. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9530-6.ch015.
Der volle Inhalt der QuellePierzchajlo, Stephen, und Jonas K. Olofsson. „Human olfaction: A view from the top“. In Sensory Individuals, 209–24. Oxford University PressOxford, 2023. http://dx.doi.org/10.1093/oso/9780198866305.003.0013.
Der volle Inhalt der QuelleG. Miathali, Poornima. „Efficient Machine Learning Classifier for Fault Detection in Wireless Sensor Networks“. In Wireless Sensor Networks - Research Issues and Effective Smart Solutions [Working Title]. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.111462.
Der volle Inhalt der QuelleMarks-Tarlow, Terry. „Intuition in a Nonlinear World“. In Chaos and Nonlinear Psychology, 243–61. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780190465025.003.0013.
Der volle Inhalt der QuelleKruger-Robbins, Benjamin. „“Holy Fruit Salad, Batman!”“. In Camp TV of the 1960s, 154—C7P100. Oxford University PressNew York, 2023. http://dx.doi.org/10.1093/oso/9780197650745.003.0008.
Der volle Inhalt der QuelleVinayakumar, R., K. P. Soman und Prabaharan Poornachandran. „Evaluation of Recurrent Neural Network and its Variants for Intrusion Detection System (IDS)“. In Deep Learning and Neural Networks, 295–316. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0414-7.ch018.
Der volle Inhalt der QuelleDickscheid, Timo, Sarah Haas, Sebastian Bludau, Philipp Glock, Marcel Huysegoms und Katrin Amunts. „Towards 3D Reconstruction of Neuronal Cell Distributions from Histological Human Brain Sections“. In Future Trends of HPC in a Disruptive Scenario. IOS Press, 2019. http://dx.doi.org/10.3233/apc190016.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Explicit content detection"
Vaglio, Andrea, Romain Hennequin, Manuel Moussallam, Gael Richard und Florence d'Alche-Buc. „Audio-Based Detection of Explicit Content in Music“. In ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020. http://dx.doi.org/10.1109/icassp40776.2020.9054278.
Der volle Inhalt der QuelleChin, Hyojin, Jayong Kim, Yoonjong Kim, Jinseop Shin und Mun Y. Yi. „Explicit Content Detection in Music Lyrics Using Machine Learning“. In 2018 IEEE International Conference on Big Data and Smart Computing (BigComp). IEEE, 2018. http://dx.doi.org/10.1109/bigcomp.2018.00085.
Der volle Inhalt der QuelleDubettier, Adrien, Tanguy Gernot, Emmanuel Giguet und Christophe Rosenberger. „A Comparative Study of Tools for Explicit Content Detection in Images“. In 2023 International Conference on Cyberworlds (CW). IEEE, 2023. http://dx.doi.org/10.1109/cw58918.2023.00077.
Der volle Inhalt der QuelleWang, Supeng, Yuxi Li, Ming Xie, Mingmin Chi, Yabiao Wang, Chengjie Wang und Wenbing Zhu. „Align, Perturb and Decouple: Toward Better Leverage of Difference Information for RSI Change Detection“. In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/166.
Der volle Inhalt der QuelleZheng, Li, Zhenpeng Li, Jian Li, Zhao Li und Jun Gao. „AddGraph: Anomaly Detection in Dynamic Graph Using Attention-based Temporal GCN“. In 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.2019/614.
Der volle Inhalt der QuelleYu, Zhiyuan, und Kwun-Lon Ting. „Explicit Dynamics Analysis for Harmonic Drives“. In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-34759.
Der volle Inhalt der QuelleAcharya, Manoj, Anirban Roy, Kaushik Koneripalli, Susmit Jha, Christopher Kanan und Ajay Divakaran. „Detecting Out-Of-Context Objects Using Graph Contextual Reasoning Network“. In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/89.
Der volle Inhalt der QuelleYu, Zhe, Di Jin, Xiaobao Wang, Yawen Li, Longbiao Wang und Jianwu Dang. „Commonsense Knowledge Enhanced Sentiment Dependency Graph for Sarcasm Detection“. In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/269.
Der volle Inhalt der QuelleLall, Pradeep, Prashant Gupta und Kai Goebel. „Failure Mode Clustering is Electronic Assemblies Using Sammon’s Mapping With Supervised Training of Perceptrons“. In ASME 2011 International Mechanical Engineering Congress and Exposition. ASMEDC, 2011. http://dx.doi.org/10.1115/imece2011-65833.
Der volle Inhalt der QuelleDu, Jiachen, Ruifeng Xu, Yulan He und Lin Gui. „Stance Classification with Target-specific Neural Attention“. In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/557.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Explicit content detection"
Rankin, Nicole, Deborah McGregor, Candice Donnelly, Bethany Van Dort, Richard De Abreu Lourenco, Anne Cust und Emily Stone. Lung cancer screening using low-dose computed tomography for high risk populations: Investigating effectiveness and screening program implementation considerations: An Evidence Check rapid review brokered by the Sax Institute (www.saxinstitute.org.au) for the Cancer Institute NSW. The Sax Institute, Oktober 2019. http://dx.doi.org/10.57022/clzt5093.
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