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المؤلفون: Tomi Raty, Timo Lintonen, Niko Reunanen, Juho Jokinen
المصدر: Reunanen, N, Räty, T, Lintonen, T & Jokinen, J 2022, ' Assessment of the Clusterability of Data Using a Multimodal Convolutional Neural Network ', IEEE Transactions on Artificial Intelligence, vol. 3, no. 3, pp. 355-369 . https://doi.org/10.1109/tai.2021.3117537
مصطلحات موضوعية: ComputingMethodologies_PATTERNRECOGNITION, Artificial neural networks, business.industry, Computer science, Pattern recognition, Artificial intelligence, business, Convolutional neural network, Convolutional neural networks (CNNs), Clustering
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bfd98a7f59dcdf7a336bc0c54ca69feb
https://doi.org/10.1109/tai.2021.3117537
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المؤلفون: Tomi Raty, Timo Lintonen, Niko Reunanen
المصدر: Reunanen, N, Räty, T & Lintonen, T 2020, ' Automatic optimization of outlier detection ensembles using a limited number of outlier examples ', International Journal of Data Science and Analytics, vol. 10, no. 4, pp. 377-394 . https://doi.org/10.1007/s41060-020-00222-4
مصطلحات موضوعية: Computer science, Applied Mathematics, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, InformationSystems_DATABASEMANAGEMENT, 02 engineering and technology, computer.software_genre, Computer Science Applications, Management information systems, ComputingMethodologies_PATTERNRECOGNITION, Computational Theory and Mathematics, 020204 information systems, Modeling and Simulation, Bagging, Outlier, 0202 electrical engineering, electronic engineering, information engineering, Outlier detection, Outlier detection ensemble, 020201 artificial intelligence & image processing, Anomaly detection, Data mining, computer, Semi-supervised outlier detection, Information Systems
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المؤلفون: Tyler Hoyt, David E. Culler, Tomi Raty, Juho Jokinen, Niko Reunanen
المصدر: Reunanen, N, Räty, T, Jokinen, J J, Hoyt, T & Culler, D 2020, ' Unsupervised online detection and prediction of outliers in streams of sensor data ', International Journal of Data Science and Analytics, vol. 9, no. 3, pp. 285-314 . https://doi.org/10.1007/s41060-019-00191-3
International Journal of Data Science and Analyticsمصطلحات موضوعية: 0301 basic medicine, Computer science, Computation, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 03 medical and health sciences, 0302 clinical medicine, EWMA chart, Latency (engineering), Representation (mathematics), business.industry, Applied Mathematics, InformationSystems_DATABASEMANAGEMENT, Pattern recognition, Autoencoder, Computer Science Applications, ComputingMethodologies_PATTERNRECOGNITION, 030104 developmental biology, Stochastic gradient descent, Computational Theory and Mathematics, 030220 oncology & carcinogenesis, Modeling and Simulation, Outlier, Anomaly detection, Artificial intelligence, business, Information Systems
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المؤلفون: Heikki Astola, Matthieu Molinier, Niko Reunanen, Tomi Raty, Arttu Lämsä
المصدر: IGARSS
Molinier, M, Reunanen, N, Lämsä, A, Astola, H & Räty, T 2018, Deepcloud-A Fully Convolutionnal Neural Network for Cloud and Shadow Masking in Optical Satellite Images . in 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018-Proceedings ., 8517484, IEEE Institute of Electrical and Electronic Engineers, pp. 2107-2110, 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018, Valencia, Spain, 22/07/18 . https://doi.org/10.1109/IGARSS.2018.8517484مصطلحات موضوعية: Masking (art), Cloud and shadow masking, 010504 meteorology & atmospheric sciences, Satellites, Computer science, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 0211 other engineering and technologies, Cloud computing, 02 engineering and technology, 01 natural sciences, Optical imaging, Clouds, Shadow, Computer vision, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Network model, fully convolutional network, ta213, Artificial neural network, Artificial satellites, business.industry, Deep learning, deep learning, Earth, Remote sensing, Computer Science::Computer Vision and Pattern Recognition, optical images, Satellite, Artificial intelligence, business, Landsat
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3f0cedba3c7f45be0bd356e01ff96f6b
https://doi.org/10.1109/igarss.2018.8517484
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