Suchergebnisse - conventional neural network-autoencoder (architektur* OR architecture*)

A deep stacked random vector functional link network autoencoder for diagnosis of brain abnormalities and breast cancer von Nayak, Deepak Ranjan, Dash, Ratnakar, Majhi, Banshidhar, Pachori, Ram Bilas, Zhang, Yudong

“… Almost all existing methods are designed using conventional machine …”
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Deep convolutional autoencoders for the time–space reconstruction of liquid rocket engine flames von Zapata Usandivaras, José F., Bauerheim, Michael, Cuenot, Bénédicte, Urbano, Annafederica

“… These methods promise to deliver where conventional linear techniques, such as Proper Orthogonal Decomposition (POD …”
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Functional autoencoder for smoothing and representation learning von Wu, Sidi, Beaulac, Cédric, Cao, Jiguo

“… representations may not be sufficient. In this study, we propose to learn the nonlinear representations of functional data using neural network autoencoders designed to process data in the form it is usually collected without the need of preprocessing …”
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Proposal of failure prediction method of factory equipment by vibration data with Recurrent Autoencoder von TAMURA, Satoshi, HAYAMIZU, Satoru, ISASHI, Ryosuke, NAITOU, Takayoshi, MATSUI, Ayaka, FURUKAWA, Akira, ASAHI, Shota

“… In this paper, we propose a method to predict the failure of factory equipment by machine learning architectures using vibration data …”
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再帰型オートエンコーダを用いた振動データによる工場設備の故障予測手法の提案 von 速水, 悟, 井指, 諒亮, 古川, 輝, 内藤, 孝昌, 朝日, 翔太, 松井, 彩華, 田村, 哲嗣

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Proposal of failure prediction method of factory equipment by vibration data with Recurrent Autoencoder von TAMURA, Satoshi, HAYAMIZU, Satoru, ISASHI, Ryosuke, NAITOU, Takayoshi, MATSUI, Ayaka, FURUKAWA, Akira, ASAHI, Shota

“… In this paper, we propose a method to predict the failure of factory equipment by machine learning architectures using vibration data …”
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Optimized intrusion detection in IoT and fog computing using ensemble learning and advanced feature selection von Tawfik, Mohammed

“… The proliferation of Internet of Things (IoT) devices and fog computing architectures has introduced major security and cyber threats …”
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Functional Autoencoder for Smoothing and Representation Learning von Wu, Sidi, Beaulac, Cédric, Cao, Jiguo

“… representations may not be sufficient. In this study, we propose to learn the nonlinear representations of functional data using neural network autoencoders designed to process data in the form it is usually collected without the need of preprocessing …”
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