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Статті в журналах з теми "Music Performance Classification Data processing"
Sudarma, Made, and I. Gede Harsemadi. "Design and Analysis System of KNN and ID3 Algorithm for Music Classification based on Mood Feature Extraction." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 1 (February 1, 2017): 486. http://dx.doi.org/10.11591/ijece.v7i1.pp486-495.
Повний текст джерелаManoharan, J. Samuel. "Audio Tagging Using CNN Based Audio Neural Networks for Massive Data Processing." December 2021 3, no. 4 (December 24, 2021): 365–74. http://dx.doi.org/10.36548/jaicn.2021.4.008.
Повний текст джерелаYang, Daniel, Kevin Ji, and TJ Tsai. "A Deeper Look at Sheet Music Composer Classification Using Self-Supervised Pretraining." Applied Sciences 11, no. 4 (February 4, 2021): 1387. http://dx.doi.org/10.3390/app11041387.
Повний текст джерелаSinghal, Rahul, Shruti Srivatsan, and Priyabrata Panda. "Classification of Music Genres using Feature Selection and Hyperparameter Tuning." September 2022 4, no. 3 (August 25, 2022): 167–78. http://dx.doi.org/10.36548/jaicn.2022.3.003.
Повний текст джерелаVani Vivekanand, Chettiyar. "Performance Analysis of Emotion Classification Using Multimodal Fusion Technique." Journal of Computational Science and Intelligent Technologies 2, no. 1 (April 16, 2021): 14–20. http://dx.doi.org/10.53409/mnaa/jcsit/2103.
Повний текст джерелаGrollmisch, Sascha, and Estefanía Cano. "Improving Semi-Supervised Learning for Audio Classification with FixMatch." Electronics 10, no. 15 (July 28, 2021): 1807. http://dx.doi.org/10.3390/electronics10151807.
Повний текст джерелаMa, Bo Le, Jing Fang Cheng, and Chao Ran Zhang. "Research on a New Array-Manifold of Single Vector Hydrophone." Advanced Materials Research 955-959 (June 2014): 899–910. http://dx.doi.org/10.4028/www.scientific.net/amr.955-959.899.
Повний текст джерелаDwisaputra, Indra, and Ocsirendi Ocsirendi. "Teknik Pengenalan Suara Musik Pada Robot Seni Tari." Manutech : Jurnal Teknologi Manufaktur 10, no. 02 (May 20, 2019): 35–39. http://dx.doi.org/10.33504/manutech.v10i02.66.
Повний текст джерелаWang, Guoxuan, Guimei Zheng, Hongzhen Wang, and Chen Chen. "Meter Wave Polarization-Sensitive Array Radar for Height Measurement Based on MUSIC Algorithm." Sensors 22, no. 19 (September 26, 2022): 7298. http://dx.doi.org/10.3390/s22197298.
Повний текст джерелаLiang, Yan, Zhou Meng, Yu Chen, Yichi Zhang, Mingyang Wang, and Xin Zhou. "A Data Fusion Orientation Algorithm Based on the Weighted Histogram Statistics for Vector Hydrophone Vertical Array." Sensors 20, no. 19 (October 1, 2020): 5619. http://dx.doi.org/10.3390/s20195619.
Повний текст джерелаДисертації з теми "Music Performance Classification Data processing"
McKay, Cory. "Automatic genre classification of MIDI recordings." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=81503.
Повний текст джерелаFiebrink, Rebecca. "An exploration of feature selection as a tool for optimizing musical genre classification /." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=99372.
Повний текст джерелаPhillips, Rhonda D. "A Probabilistic Classification Algorithm With Soft Classification Output." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/26701.
Повний текст джерелаPh. D.
Sanden, Christopher, and University of Lethbridge Faculty of Arts and Science. "An empirical evaluation of computational and perceptual multi-label genre classification on music / Christopher Sanden." Thesis, Lethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer Science, c2010, 2010. http://hdl.handle.net/10133/2602.
Повний текст джерелаviii, 87 leaves ; 29 cm
Klinkradt, Bradley Hugh. "An investigation into the application of the IEEE 1394 high performance serial bus to sound installation contro." Thesis, Rhodes University, 2003. http://hdl.handle.net/10962/d1004899.
Повний текст джерелаKMBT_363
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Jürgensen, Frauke. "Accidentals in the mid-fifteenth century : a computer-aided study of the Buxheim organ book and its concordances." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=85921.
Повний текст джерелаLaurier, Cyril François. "Automatic Classification of musical mood by content-based analysis." Doctoral thesis, Universitat Pompeu Fabra, 2011. http://hdl.handle.net/10803/51582.
Повний текст джерелаEn esta tesis, nos centramos en la clasificación automática de música a partir de la detección de la emoción que comunica. Primero, estudiamos cómo los miembros de una red social utilizan etiquetas y palabras clave para describir la música y las emociones que evoca, y encontramos un modelo para representar los estados de ánimo. Luego, proponemos un método de clasificación automática de emociones. Analizamos las contribuciones de descriptores de audio y cómo sus valores están relacionados con los estados de ánimo. Proponemos también una versión multimodal de nuestro algoritmo, usando las letras de canciones. Finalmente, después de estudiar la relación entre el estado de ánimo y el género musical, presentamos un método usando la clasificación automática por género. A modo de recapitulación conceptual y algorítmica, proponemos una técnica de extracción de reglas para entender como los algoritmos de aprendizaje automático predicen la emoción evocada por la música
Kästel, Arne Morten, and Christian Vestergaard. "Comparing performance of K-Means and DBSCAN on customer support queries." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-260252.
Повний текст джерелаI kundtjänst förekommer det ofta upprepningar av frågor samt sådana frågor som inte kräver unika svar. I syfte att öka produktiviteten i kundtjänst funktionens arbete att besvara dessa frågor undersöks metoder för att automatisera en del av arbetet. Vi undersöker olika metoder för klusteranalys, applicerat på existerande korpusar innehållande texter så väl som frågor. Klusteranalysen genomförs i syfte att identifiera dokument som är semantiskt lika, vilket i ett automatiskt system för frågebevarelse skulle kunna användas för att besvara en ny fråga med ett existerande svar. En jämförelse mellan hur K-means och densitetsbaserad metod presterar på tre olika korpusar vars dokumentrepresentationer genererats med BERT genomförs. Vidare diskuteras den digitala transformationsprocessen, varför företag misslyckas avseende implementation samt även möjligheterna för en ny mer iterativ modell.
Shafer, Seth. "Recent Approaches to Real-Time Notation." Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc984210/.
Повний текст джерелаBayle, Yann. "Apprentissage automatique de caractéristiques audio : application à la génération de listes de lecture thématiques." Thesis, Bordeaux, 2018. http://www.theses.fr/2018BORD0087/document.
Повний текст джерелаThis doctoral dissertation presents, discusses and proposes tools for the automatic information retrieval in big musical databases.The main application is the supervised classification of musical themes to generate thematic playlists.The first chapter introduces the different contexts and concepts around big musical databases and their consumption.The second chapter focuses on the description of existing music databases as part of academic experiments in audio analysis.This chapter notably introduces issues concerning the variety and unequal proportions of the themes contained in a database, which remain complex to take into account in supervised classification.The third chapter explains the importance of extracting and developing relevant audio features in order to better describe the content of music tracks in these databases.This chapter explains several psychoacoustic phenomena and uses sound signal processing techniques to compute audio features.New methods of aggregating local audio features are proposed to improve song classification.The fourth chapter describes the use of the extracted audio features in order to sort the songs by themes and thus to allow the musical recommendations and the automatic generation of homogeneous thematic playlists.This part involves the use of machine learning algorithms to perform music classification tasks.The contributions of this dissertation are summarized in the fifth chapter which also proposes research perspectives in machine learning and extraction of multi-scale audio features
Книги з теми "Music Performance Classification Data processing"
1946-, Beall Julianne, ed. DDC, Dewey decimal classification: 004-006 data processing and computer science and changes in related disciplines. Albany, NY: Forest Press, Division of the Lake Placid Education Foundation, 1985.
Знайти повний текст джерелаDewey, Melvil. DDC, Dewey decimal classification.: Revision of edition 19. Albany, N.Y., U.S.A: Forest Press, 1985.
Знайти повний текст джерелаThe sound on sound book of live sound for the performing musician. London: Sanctuary Publishing, 1998.
Знайти повний текст джерелаOffice, General Accounting. District of Columbia: Comments on fiscal year 2000 performance report : report to congressional subcommittees. Washington, D.C: U.S. General Accounting Office, 2001.
Знайти повний текст джерелаOffice, General Accounting. District of Columbia: Performance report reflects progress and opportunities for improvement : report to congressional subcommittees. [Washington, D.C.]: The Office, 2002.
Знайти повний текст джерелаGabrielli, Leonardo, and Stefano Squartini. Wireless Networked Music Performance. Springer Singapore Pte. Limited, 2016.
Знайти повний текст джерелаGabrielli, Leonardo, and Stefano Squartini. Wireless Networked Music Performance. Springer London, Limited, 2016.
Знайти повний текст джерелаGuide To Computing For Expressive Music Performance. Springer, 2012.
Знайти повний текст джерелаMak, Kitman, and Chris Frost. A. I. Performance : the Art of Live Automation: The Ultimate 'how to' Guide in Creating Stunning, Technical and Revolutionary Live Shows for Any Contemporary Musical Performer. Independently Published, 2018.
Знайти повний текст джерелаMak, Kitman, and Chris Frost. A. I. Performance : The Art of Live Automation: The Ultimate 'how to' Guide in Creating Stunning, Technical and Revolutionary Live Shows for Any Contemporary Musical Performer. Independently Published, 2018.
Знайти повний текст джерелаЧастини книг з теми "Music Performance Classification Data processing"
Vatolkin, Igor, Wolfgang Theimer, and Martin Botteck. "Partition Based Feature Processing for Improved Music Classification." In Challenges at the Interface of Data Analysis, Computer Science, and Optimization, 411–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24466-7_42.
Повний текст джерелаKralj Novak, Petra, Teresa Scantamburlo, Andraž Pelicon, Matteo Cinelli, Igor Mozetič, and Fabiana Zollo. "Handling Disagreement in Hate Speech Modelling." In Information Processing and Management of Uncertainty in Knowledge-Based Systems, 681–95. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08974-9_54.
Повний текст джерела"Classification performance of data mining algorithms applied to breast cancer data." In Computational Vision and Medical Image Processing IV, 325–30. CRC Press, 2013. http://dx.doi.org/10.1201/b15810-58.
Повний текст джерелаZhu, Qiusha, Lin Lin, Mei-Ling Shyu, and Dianting Liu. "Utilizing Context Information to Enhance Content-Based Image Classification." In Multimedia Data Engineering Applications and Processing, 114–30. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2940-0.ch006.
Повний текст джерелаMeng, Tao, Mei-Ling Shyu, and Lin Lin. "Multimodal Information Integration and Fusion for Histology Image Classification." In Multimedia Data Engineering Applications and Processing, 35–50. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2940-0.ch003.
Повний текст джерелаTarle, Balasaheb, and M. Akkalakshmi. "Integrating Multiple Techniques to Enhance Medical Data Classification." In Advances in Systems Analysis, Software Engineering, and High Performance Computing, 252–74. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-9121-5.ch012.
Повний текст джерелаJoshi, Deepak, and Michael E. Hahn. "Electromyogram and Inertial Sensor Signal Processing in Locomotion and Transition Classification." In Data Analytics in Medicine, 762–78. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1204-3.ch041.
Повний текст джерелаWeese, Josh. "Predictive Analytics in Digital Signal Processing." In Advances in Data Mining and Database Management, 223–53. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-5063-3.ch010.
Повний текст джерелаSingh, Deepak, Dilip Singh Sisodia, and Pradeep Singh. "Genetic Algorithm Based Pre-Processing Strategy for High Dimensional Micro-Array Gene Classification." In Nature-Inspired Algorithms for Big Data Frameworks, 22–46. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-5852-1.ch002.
Повний текст джерелаBaharadwaj, Nitin, Sheena Wadhwa, Pragya Goel, Isha Sethi, Chanpreet Singh Arora, Aviral Goel, Sonika Bhatnagar, and Harish Parthasarathy. "De-Noising, Clustering, Classification, and Representation of Microarray Data for Disease Diagnostics." In Research Developments in Computer Vision and Image Processing, 149–74. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-4558-5.ch009.
Повний текст джерелаТези доповідей конференцій з теми "Music Performance Classification Data processing"
Silva, Diego Furtado, Angelo Cesar Mendes da Silva, Luís Felipe Ortolan, and Ricardo Marcondes Marcacini. "On Generalist and Domain-Specific Music Classification Models and Their Impacts on Brazilian Music Genre Recognition." In Simpósio Brasileiro de Computação Musical. Sociedade Brasileira de Computação - SBC, 2021. http://dx.doi.org/10.5753/sbcm.2021.19427.
Повний текст джерелаPanchwagh, Mangesh M., and Vijay D. Katkar. "Music genre classification using data mining algorithm." In 2016 Conference on Advances in Signal Processing (CASP). IEEE, 2016. http://dx.doi.org/10.1109/casp.2016.7746136.
Повний текст джерелаEr, Mehmet Bilal, Harun CIg, and Umut Kuran. "Classification of Makam structures in Turkish art music with using artificial neural network." In 2017 International Artificial Intelligence and Data Processing Symposium (IDAP). IEEE, 2017. http://dx.doi.org/10.1109/idap.2017.8090276.
Повний текст джерелаMcKay, Cory, and Ichiro Fujinaga. "Improving automatic music classification performance by extracting features from different types of data." In the international conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1743384.1743430.
Повний текст джерелаSuryaprakash, Raj Tejas, and Raj Rao Nadakuditi. "The performance of music-based DOA in white noise with missing data." In 2012 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2012. http://dx.doi.org/10.1109/ssp.2012.6319826.
Повний текст джерелаShimamura, Tetsuya, and Takeshi Yokose. "AR-model-based data extension to improve the Performance of MUSIC." In 2013 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS). IEEE, 2013. http://dx.doi.org/10.1109/ispacs.2013.6704593.
Повний текст джерелаPavlopoulou, Christina, and Stella X. Yu. "Classification and feature selection with human performance data." In 2010 17th IEEE International Conference on Image Processing (ICIP 2010). IEEE, 2010. http://dx.doi.org/10.1109/icip.2010.5650308.
Повний текст джерелаPowell, Harry C., John Lach, Maite Brandt-Pearce, and Charles L. Brown. "Systematic estimation of ANN classification performance employing synthetic data." In 2010 IEEE International Workshop on Machine Learning for Signal Processing (MLSP). IEEE, 2010. http://dx.doi.org/10.1109/mlsp.2010.5589207.
Повний текст джерелаDas, Madhusmita, and Rasmita Dash. "Performance Analysis of Classification Techniques for Car Data Set Analysis." In 2020 International Conference on Communication and Signal Processing (ICCSP). IEEE, 2020. http://dx.doi.org/10.1109/iccsp48568.2020.9182332.
Повний текст джерелаErkaymaz, Okan, and Tugba Palabas. "Classification of cervical cancer data and the effect of random subspace algorithms on classification performance." In 2018 26th Signal Processing and Communications Applications Conference (SIU). IEEE, 2018. http://dx.doi.org/10.1109/siu.2018.8404197.
Повний текст джерела