Suchergebnisse - Modified stacked denoising autoencoder

Stepwise inertial intelligent control for wind power frequency support based on modified stacked denoising autoencoder von Zhou, Tao, Wang, Yalun, Quan, Hao, Zhang, Teng

“… Due to the large-scale popularization of renewable energy, the rotational inertia of modern power system is reduced, which increases the risk of power system …”
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Sediment Classification of Acoustic Backscatter Image Based on Stacked Denoising Autoencoder and Modified Extreme Learning Machine von Zhou, Ping, Chen, Gang, Wang, Mingwei, Chen, Jifa, Li, Yizhe

“… Therefore, we propose a sediment classification method based on the acoustic backscatter image by combining a stacked denoising auto encoder (SDAE …”
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Modified metaheuristics with stacked sparse denoising autoencoder model for cervical cancer classification von Vaiyapuri, Thavavel, Alaskar, Haya, Syed, Liyakathunisa, Aljohani, Eman, Alkhayyat, Ahmed, Shankar, K., Kumar, Sachin

“… •Propose modified firefly optimization algorithm for hyperparameter tuning.•Validate the performance of proposed model on Herlev database …”
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Heartbeat classification system based on modified stacked denoising autoencoders and neural networks von Chaoyan Jiang, Shuang Song, Meng, Max Q.-H

“… This paper introduces a complete heartbeat classification system based on modified stacked denoising autoencoders and neural networks …”
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Denoising Letter Images from Scanned Invoices Using Stacked Autoencoders von Ibrahim, Muhammad, Hanif, Muhammad, Ahmad, Shabir, Jamil, Faisal, Sehar, Tayyaba, Lee, YunJung, Kim, DoHyeun

“… A stacked denoising autoencoder (SDAE) is implemented with two hidden layers each in encoder network and decoder network …”
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Fault Diagnosis for Hydraulic Servo System: A Stacked Denoising Autoencoder Method based on Self-Learning of Robustness Features von Wang, Zhenya, Fan, Jiaxuan, Huang, Hu, Han, Te

“… Thus this paper proposes a stacked deep learning based model to represent robust feature information in terms of the advantage of cognitive computing and pattern classification theory, which is shown …”
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Probabilistic Stacked Denoising Autoencoder for Power System Transient Stability Prediction With Wind Farms von Su, Tong, Liu, Youbo, Zhao, Junbo, Liu, Junyong

“… To address the uncertainties of renewable energy and loads in transient stability assessment with credible contingencies, this letter proposes a stacked denoising autoencoder (SDAE …”
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Object detection and tracking under Complex environment using deep learning-based LPM von Li, Yundong, Zhang, Xueyan, Li, Hongguang, Zhou, Qichen, Cao, Xianbin, Xiao, Zhifeng

“… Object detection and tracking under complex environment are challenging because of the disturbances induced by background clutter, illumination changes, …”
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An Automatic Cardiac Arrhythmia Classification System With Wearable Electrocardiogram von Xia, Yufa, Zhang, Huailing, Xu, Lin, Gao, Zhifan, Zhang, Heye, Liu, Huafeng, Li, Shuo

“… This paper presents an automatic wearable electrocardiogram (ECG) classification and monitoring system with stacked denoising autoencoder (SDAE …”
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Adaptive marginalized stacked denoising autoencoders and its application von Yu, Zhi-bin, Chen, Chun-xia, Pang, Rong, Chen, Tao-wei

“… In this paper, we propose a modified marginalized autoencoders. Here, the noise adding way at a fixed rate in marginalized autoencoders is replaced by the adaptive noise injection …”
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Ensemble deep transfer learning driven by multisensor signals for the fault diagnosis of bevel-gear cross-operation conditions von Di, ZiYang, Shao, HaiDong, Xiang, JiaWei

“… First, a novel stacked autoencoder (NSAE) is constructed using a denoising autoencoder, batch normalization, and the Swish activation function …”
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Cycle life test optimization for different Li-ion power battery formulations using a hybrid remaining-useful-life prediction method von Ma, Jian, Xu, Shu, Shang, Pengchao, ding, Yu, Qin, Weili, Cheng, Yujie, Lu, Chen, Su, Yuzhuan, Chong, Jin, Jin, Haizu, Lin, Yongshou

“… •Deep learning is used to predict battery lifespan in high-temperature testing.•The transfer learning method is based on a stacked denoising autoencoder …”
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Revolutionizing emergency vehicle response: a smart traffic management approach with adaptive CNN and hybrid deep learning von Vikraman, Bindu Puthentharayil, Mahadevan, Vanitha, Jabbar, Rani Fathima

“… ), which has been optimized with the Enhanced walrus optimization (EWO) algorithm. In addition, a hybrid deep learning model is used to identify emergency vehicles, with Stacked AutoEncoder (SAE …”
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Data-Driven Dynamic Security Partition Assessment of Power Systems Based on Symmetric Electrical Distance Matrix and Chebyshev Distance von Qi, Hang, Su, Ruiyang, Sun, Runjia, Yan, Jiongcheng

“… Secondly, high-level features of operating conditions are extracted based on the stacked denoising autoencoder …”
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Hierarchical feature exttratction for object recogition in complex SAR image using modified convolutional auto-encoder von Tian, S.R., Wang, C., Zhang, H.

“… In this paper, a feature extraction method based on modified stacked convolutional denoising auto-encoder (MSCDAE …”
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Complete Stacked Denoising Auto-Encoders for Regression von Fernández-García, María-Elena, Sancho-Gómez, José-Luis, Ros-Ros, Antonio, Figueiras-Vidal, Aníbal R.

“… Complete modified stacked denoising auto-encoder (CMSDAE) machines constitute a version of stacked auto-encoders in which a target estimate is included …”
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Cross-domain sentiment classification using deep learning approach von Miao Sun, Qi Tan, Runwei Ding, Hong Liu

“… In this paper, we firstly propose a modified version of marginalized stacked denoising autoencoders (mSDA). We call it mSDA++ …”
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A New Pan-Sharpening Method With Deep Neural Networks von Huang, Wei, Xiao, Liang, Wei, Zhihui, Liu, Hongyi, Tang, Songze

“… Inspired by this observation, a modified sparse denoising autoencoder (MSDA) algorithm is proposed to train the relationship between high-resolution (HR …”
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Secure and Privacy-Preserving Framework for IoT-Enabled Smart Grid Environment von Kumar, Chandan, Chittora, Prakash

“… Due to recent technical breakthroughs in wireless communication and the Internet of Things (IoT), the smart grid (SG) has been recognized as a next-generation …”
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An On-Line and Adaptive Method for Detecting Abnormal Events in Videos Using Spatio-Temporal ConvNet von Bouindour, Samir, Snoussi, Hichem, Hittawe, Mohamad Mazen, Tazi, Nacef, Wang, Tian

“… In this context, we use only normal events as training samples. We propose to use a modified version of pretrained 3D residual convolutional network to extract spatio-temporal …”
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