1,743 resources related to Unsupervised learning
- Topics related to Unsupervised learning
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- Most published Xplore authors for Unsupervised learning
2013 International Conference on Machine Learning and Cybernetics (ICMLC)
Statistical Machine Learning, Intelligent & fuzzy control, Pattern Recognition , Ensemble method, Evolutionary computation, Fuzzy & rough set, Data & web mining , Intelligent Business Computing , Biometrics , Bioinformatics , Information retrieval, Cybersecurity, Web intelligence and technology, Semantics & ontology engineering, Social Networks & Ubiquitous Intelligence, Multicriteria decision making, Soft Computing, Intelligent Systems, Speech, Image & Video Processing, Decision Support System
2012 10th World Congress on Intelligent Control and Automation (WCICA 2012)
A. Intelligent Control B. Control Theory and Control Engineering C. Complex Systems and Intelligent Robots D. Others
Theoretical advances, applications and ideas in the fields of information theory (including application to biological sciences); communication, networking, signal, image and video processing; systems and control; learning and statistical inference.
2012 IEEE 15th International Conference on Computational Science and Engineering (CSE)
The Computational Science and Engineering area has earned prominence through advances in electronic and integrated technologies beginning in the 1940s. Current times are very exciting and the years to come will witness a proliferation in the use of various advanced computing systems. It is increasingly becoming an emerging and promising discipline in shaping future research and development activities in academia and industry, ranging from engineering, science, finance, economics, arts and humanitarian fields, especially when the solution of large and complex problems must cope with tight timing schedules.
Artificial intelligence techniques, including speech, voice, graphics, images, and documents; knowledge and data engineering tools and techniques; parallel and distributed processing; real-time distributed processing; system architectures, integration, and modeling; database design, modeling, and management; query design, and implementation languages; distributed database control; statistical databases; algorithms for data and knowledge management; performance evaluation of algorithms and systems; data communications aspects; system ...
Christodoulou, C.I.; Pattichis, C.S. Neural Networks, 1995. Proceedings., IEEE International Conference on, 1995
The shapes and firing rates of motor unit action potentials (MUAPs) in an electromyographic (EMG) signal provide an important source of information for the diagnosis of neuromuscular disorders. In order to extract this information from EMG signals recorded at force levels up to 20% of maximum voluntary contraction (MVC) it is required: (i) To identify the MUAPs composing the EMG ...
Somervuo, P. Neural Networks, 1999. IJCNN '99. International Joint Conference on, 1999
Time information of the input data is used for evaluating the goodness of the self-organizing map to store and represent temporal feature vector sequences. A new node neighborhood is defined for the map which takes the temporal order of the input samples into account. A connection is created between those two map modes which are the best-matching units for two ...
Nurunnabi, A.A.M.; Nasser, M. Computer and Information Technology, 2008. ICCIT 2008. 11th International Conference on, 2008
ldquoLearning methodsrdquo play a key role in the fields of statistics, data mining, and artificial intelligence, intersecting with areas of engineering and other disciplines. These methods for analyzing and modeling data come in two flavors: supervised and unsupervised learning. Regression analysis and classification are two well known supervised learning techniques. To get an effective model from regression analysis it is ...
Tamersoy, B.; Aggarwal, J.K. Advanced Video and Signal Based Surveillance, 2009. AVSS '09. Sixth IEEE International Conference on, 2009
This paper presents a novel approach to vehicle detection in highway surveillance videos. This method incorporates well-studied computer vision and machine learning techniques to form an unsupervised system, where vehicles are automatically ldquolearnedrdquo from video sequences. First an enhanced adaptive background mixture model is used to identify positive and negative examples. Then a classifier is trained with these examples. In ...
Cermuschi-Frais, B.; Segura, E.C. Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on, 2000
We study, using standard Probability Theory results, the ability of the Hopfield model of associative memory using the Hebb rule to learn mean values from examples in the presence of noise. We state and prove properties concerning this ability
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