Search Results - "Deep convolutional autoencoder (CAE)"

Intelligent framework for unsupervised damage detection in bridges using deep convolutional autoencoder with wavelet transmissibility pattern spectra by Li, Shuai, Cao, Yuxi, Gdoutos, Emmanuel E., Tao, Mei, Faisal Alkayem, Nizar, Avci, Onur, Cao, Maosen

“…Deep Learning has been increasingly utilized in structural damage detection. Existing relevant studies often highlight the benefits of supervised deep learning…”
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Unsupervised Hyperspectral Image Band Selection Based on Deep Subspace Clustering by Zeng, Meng, Cai, Yaoming, Cai, Zhihua, Liu, Xiaobo, Hu, Peng, Ku, Junhua

“…Hyperspectral image (HSI) consists of hundreds of continuous narrow bands with high redundancy, resulting in the curse of dimensionality and an increased…”
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Content-based image retrieval for the diagnosis of myocardial perfusion imaging using a deep convolutional autoencoder by Higaki, Akinori, Kawaguchi, Naoto, Kurokawa, Tsukasa, Okabe, Hikaru, Kazatani, Takuro, Kido, Shinsuke, Aono, Tetsuya, Matsuda, Kensho, Tanaka, Yuta, Hosokawa, Saki, Kosaki, Tetsuya, Kawamura, Go, Shigematsu, Tatsuya, Kawada, Yoshitaka, Hiasa, Go, Yamada, Tadakatsu, Okayama, Hideki

“… We tested the feasibility of feature extraction from MPI using a deep convolutional autoencoder (CAE) model…”
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Deep convolutional autoencoder for radar-based classification of similar aided and unaided human activities by Seyfioglu, Mehmet Saygin, Ozbayoglu, Ahmet Murat, Gurbuz, Sevgi Zubeyde

“… Moreover, a three-layer, deep convolutional autoencoder (CAE) is proposed, which utilizes unsupervised pretraining to initialize the weights in the subsequent convolutional layers…”
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Deep density-based image clustering by Ren, Yazhou, Wang, Ni, Li, Mingxia, Xu, Zenglin

“…) framework to address these issues. The first stage is to train a deep convolutional autoencoder (CAE…”
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Time-frequency informed stacked long short-term memory-based generative adversarial network for missing data imputation in sensor networks by Wang, Zixin, Kachireddy, Malleswari, Mondal, Tarutal Ghosh, Tang, Wen, Jahanshahi, Mohammad R.

“…To monitor the health condition of civil infrastructures, the continuous acquisition of high-quality sensor data is crucial. However, in harsh environments,…”
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Improved AutoEncoder With LSTM Module and KL Divergence for Anomaly Detection by Huang, Wei, Zhang, Bingyang, Zhang, Kaituo, Gao, Hua, Wan, Rongchun

“… Models such as deep Convolutional AutoEncoder (CAE) and deep support vector data description (SVDD…”
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Deep semi-supervised electricity theft detection in AMI for sustainable and secure smart grids by Qi, Ruobin, Li, Qingqing, Luo, Zhirui, Zheng, Jun, Shao, Sihua

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Online quantitative monitoring of milling cutter health condition based on deep convolutional autoencoder by Lei, Yuncong, Li, Changgen, Guo, Liang, Gao, Hongli, Liang, Junhua, Sun, Yi, He, Jigang

“…) is proposed based on a deep convolutional autoencoder (CAE). In this method, a health indicator (HI…”
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Deep Character-Level Anomaly Detection Based on a Convolutional Autoencoder for Zero-Day Phishing URL Detection by Bu, Seok-Jun, Cho, Sung-Bae

“… Taken together, to ensure both sustainability and intelligibility, we propose the combination of a convolution operation to model the character-level URL features and a deep convolutional autoencoder (CAE…”
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Cross-domain learning for pulmonary nodule detection using Gestalt principle of similarity by Susan, Seba, Sethi, Dhaarna, Arora, Kriti

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Data Driven Methods for Electricity Theft Detection in Advanced Metering Infrastructure by Qi, Ruobin

“…The Advanced Metering Infrastructure (AMI) is a critical component of modern smart grids, collecting vast amounts of high-frequency power consumption data from…”
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Unsupervised Deep Learning for GPS-Based Transportation Mode Identification by Markos, Christos, Yu, James J.Q.

“… Specifically, we first pretrain a deep Convolutional AutoEncoder (CAE) using unlabeled fixed-size trajectory segments…”
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Deep Learning Based Nonlinear Dimensionality Reduction for Emulators of Numerical Thermosphere Density Models by Licata, Richard J., Mehta, Piyush M.

“…Modeling and forecasting of atmospheric drag for space objects in low Earth orbit (LEO) is a critical challenge for space situational awareness and environment…”
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Improved AutoEncoder with LSTM module and KL divergence by Huang, Wei, Zhang, Bingyang, Zhang, Kaituo, Gao, Hua, Wan, Rongchun

“… Models such as deep convolutional autoencoder (CAE) network and deep supporting vector data description (SVDD…”
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An efficient compression of ECG signals using deep convolutional autoencoders by Yildirim, Ozal, Tan, Ru San, Acharya, U. Rajendra

“… •An efficient ECG compression method based on deep convolutional autoencoders (CAE).•A deep network structure of 27 layers consisting of encoder and decoder parts…”
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Compression of EMG Signals Using Deep Convolutional Autoencoders by Dinashi, Kimia, Ameri, Ali, Akhaee, Mohammad Ali, Englehart, Kevin, Scheme, Erik

“… As a solution, this work proposes a new method for EMG data compression using deep convolutional autoencoders (CAE…”
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Delamination prediction in composite panels using unsupervised-feature learning methods with wavelet-enhanced guided wave representations by Rautela, Mahindra, Senthilnath, J., Monaco, Ernesto, Gopalakrishnan, S.

“…With the introduction of damage tolerance-based design philosophies, the demand for reliable and robust structural health monitoring (SHM) procedures for…”
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Deep Convolutional Autoencoder Applied for Noise Reduction in Range-Doppler Maps of FMCW Radars by de Oliveira, Marcio L. Lima, Bekooij, Marco J. G.

“…In this paper, we discuss the usage of deep Convolutional Autoencoders (CAE) for denoising Range-Doppler (RD…”
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Generating Synthetic Short-Range FMCW Range-Doppler Maps Using Generative Adversarial Networks and Deep Convolutional Autoencoders by de Oliveira, Marcio L. Lima, Bekooij, Marco J. G.

“…In this paper, we discuss the usage of Generative Adversarial Networks (GANs) and Deep Convolutional Autoen-coders (CAE) for creating synthetic Range-Doppler…”
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