Suchergebnisse - "Stacked autoencoder"

Financial portfolio optimization with online deep reinforcement learning and restricted stacked autoencoder—DeepBreath von Soleymani, Farzan, Paquet, Eric

“… •Extracting high-level features using restricted stacked autoencoder.•A convolutional neural network is employed to enforce the policy …”
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Learning Compact and Discriminative Stacked Autoencoder for Hyperspectral Image Classification von Zhou, Peicheng, Han, Junwei, Cheng, Gong, Zhang, Baochang

“… To address this issue, this paper proposes an effective framework, named compact and discriminative stacked autoencoder (CDSAE …”
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Prediction of potential miRNA–disease associations based on stacked autoencoder von Wang, Chun-Chun, Li, Tian-Hao, Huang, Li, Chen, Xing

“… In this study, we proposed a computational model named Stacked Autoencoder for potential MiRNA …”
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Modified Stacked Autoencoder Using Adaptive Morlet Wavelet for Intelligent Fault Diagnosis of Rotating Machinery von Shao, Haidong, Xia, Min, Wan, Jiafu, de Silva, Clarence W.

“… In this article, a modified stacked autoencoder (MSAE) that uses adaptive Morlet wavelet is proposed to automatically diagnose various fault types and severities of rotating machinery …”
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A model-based collaborate filtering algorithm based on stacked AutoEncoder von Yu, Miao, Quan, Tianqi, Peng, Qinglong, Yu, Xu, Liu, Lei

“… This paper proposes a Model-based Collaborate Filtering Algorithm Based on Stacked AutoEncoder (MCFSAE …”
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Semisupervised Stacked Autoencoder With Cotraining for Hyperspectral Image Classification von Zhou, Shaoguang, Xue, Zhaohui, Du, Peijun

“… In this paper, we present a novel DL framework, namely, semisupervised stacked autoencoders (Semi-SAEs) with cotraining, for HSI classification …”
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Unsupervised Pre-training of a Deep LSTM-based Stacked Autoencoder for Multivariate Time Series Forecasting Problems von Sagheer, Alaa, Kotb, Mostafa

“… Currently, most real-world time series datasets are multivariate and are rich in dynamical information of the underlying system. Such datasets are attracting …”
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A Computational-Based Method for Predicting Drug-Target Interactions by Using Stacked Autoencoder Deep Neural Network von Wang, Lei, You, Zhu-Hong, Chen, Xing, Xia, Shi-Xiong, Liu, Feng, Yan, Xin, Zhou, Yong, Song, Ke-Jian

“… In this article, we propose a new computational method for predicting DTIs from drug molecular structure and protein sequence by using the stacked autoencoder of deep learning, which can adequately …”
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Deep Spatio-Temporal Representation for Detection of Road Accidents Using Stacked Autoencoder von Singh, Dinesh, Mohan, Chalavadi Krishna

“… Vision-based detection of road accidents using traffic surveillance video is a highly desirable but challenging task. In this paper, we propose a novel …”
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A Novel Double-Stacked Autoencoder for Power Transformers DGA Signals With An Imbalanced Data Structure von Yang, Dongsheng, Qin, Jia, Pang, Yongheng, Huang, Tingwen

“… To fill this research gap, in this article, a novel double-stacked autoencoder (DSAE) is proposed for a fast and accurate judgment of power transformer health conditions with an imbalanced data structure …”
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Novel segmented stacked autoencoder for effective dimensionality reduction and feature extraction in hyperspectral imaging von Zabalza, Jaime, Ren, Jinchang, Zheng, Jiangbin, Zhao, Huimin, Qing, Chunmei, Yang, Zhijing, Du, Peijun, Marshall, Stephen

“… Stacked autoencoders (SAEs), as part of the deep learning (DL) framework, have been recently proposed for feature extraction in hyperspectral remote sensing …”
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Fusing stacked autoencoder and long short-term memory for regional multistep-ahead flood inundation forecasts von Kao, I-Feng, Liou, Jia-Yi, Lee, Meng-Hsin, Chang, Fi-John

“… •Use Stacked Autoencoder (SAE) to reduce the dimension of regional inundation data …”
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Obstacle Detection for Intelligent Transportation Systems Using Deep Stacked Autoencoder and k -Nearest Neighbor Scheme von Dairi, Abdelkader, Harrou, Fouzi, Ying Sun, Senouci, Mohamed

“… Obstacle detection is an essential element for the development of intelligent transportation systems so that accidents can be avoided. In this paper, we …”
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A new unsupervised data mining method based on the stacked autoencoder for chemical process fault diagnosis von Zheng, Shaodong, Zhao, Jinsong

“… : feature extraction by the convolutional stacked autoencoder (SAE), feature …”
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δ-agree AdaBoost stacked autoencoder for short-term traffic flow forecasting von Zhou, Teng, Han, Guoqiang, Xu, Xuemiao, Lin, Zhizhe, Han, Chu, Huang, Yuchang, Qin, Jing

“… Recently, the stacked autoencoder has been proven promising for traffic flow forecasting but still exists some drawbacks in certain conditions …”
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Transfer learning based on improved stacked autoencoder for bearing fault diagnosis von Luo, Shuyang, Huang, Xufeng, Wang, Yanzhi, Luo, Rongmin, Zhou, Qi

“… Stacked autoencoder (SAE) has been widely employed in deep transfer learning research since it is a semi-supervised algorithm …”
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Classification and diagnosis of cervical cancer with softmax classification with stacked autoencoder von Adem, Kemal, Kiliçarslan, Serhat, Cömert, Onur

“… Softmax classification with stacked autoencoder, one of the deep learning methods, has been used to classify data sets …”
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High-Voltage Circuit Breaker Fault Diagnosis Using a Hybrid Feature Transformation Approach Based on Random Forest and Stacked Autoencoder von Ma, Suliang, Chen, Mingxuan, Wu, Jianwen, Wang, Yuhao, Jia, Bowen, Jiang, Yuan

“… In recent years, machine learning techniques have been applied to test the fault type in high-voltage circuit breakers (HVCBs). Most related research involves …”
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Hourly PM2.5 concentration forecast using stacked autoencoder model with emphasis on seasonality von Bai, Yun, Li, Yong, Zeng, Bo, Li, Chuan, Zhang, Jin

“… Considering strong seasonal variation in meteorological conditions, in this paper, a seasonal stacked autoencoder model combining seasonal analysis and deep feature learning is proposed for forecasting the hourly PM …”
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Diagnosis of breast cancer with Stacked autoencoder and Subspace kNN von Adem, Kemal

“… In this study, an approach is proposed in which a Subspace kNN algorithm is used together with Stacked autoencoder (SAE …”
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