Suchergebnisse - Sparse stacked autoencoder network

Predicting protein-protein interactions from protein sequences by a stacked sparse autoencoder deep neural network von Wang, Yan-Bin, You, Zhu-Hong, Li, Xiao, Jiang, Tong-Hai, Chen, Xing, Zhou, Xi, Wang, Lei

“… ). Then, these extracted features were reconstructed using the stacked autoencoder. Finally, a novel …”
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Deep network approach with stacked sparse autoencoders in detection of DDoS attacks on SDN-based VANET von Polat, Huseyin, Turkoglu, Muammer, Polat, Onur

“… In this study, the stacked sparse autoencoder (SSAE) + Softmax classifier deep network model is proposed to detect DDoS attacks targeting SDN-based VANETs …”
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Parameter identification for nonlinear Hammerstein models with stacked sparse autoencoder network von Li, Feng, Song, Liexin, Wang, Tianhu, Liu, Ranran

“… In this paper, a novel parameter identification method is addressed for Hammerstein nonlinear model with stacked sparse autoencoder (SSAE) network …”
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Sparse stacked autoencoder network for complex system monitoring with industrial applications von Deng, Ziwei, Li, Yuxuan, Zhu, Hongqiu, Huang, Keke, Tang, Zhaohui, Wang, Zhen

“… •Deep learning model formed by AE with sparse and regular constraints can well extract features …”
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Reliable Fault Diagnosis of Rotary Machine Bearings Using a Stacked Sparse Autoencoder-Based Deep Neural Network von Sohaib, Muhammad, Kim, Jong-Myon

“… In this study, using complex envelope spectra and stacked sparse autoencoder …”
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A deep learning based malicious module identification using stacked sparse autoencoder network for VLSI circuit reliability von Priyatharishini, M., Nirmala Devi, M.

“… •More suitable features are extracted using handcrafted algorithms and structural reports.•Stacked autoencoder and stacked sparse autoencoder model is used to discover the malicious logic in the gate level netlist …”
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An industrial process fault diagnosis method based on independent slow feature analysis and stacked sparse autoencoder network von Li, Chang, Wen, Chenglin, Zhou, Zhe

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Breath analysis based early gastric cancer classification from deep stacked sparse autoencoder neural network von Aslam, Muhammad Aqeel, Xue, Cuili, Chen, Yunsheng, Zhang, Amin, Liu, Manhua, Wang, Kan, Cui, Daxiang

“… In this study, we proposed a new method for feature extraction using a stacked sparse autoencoder to extract the discriminative features from the unlabeled data of breath samples …”
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Novel Pelican Optimization Algorithm (POA) With Stacked Sparse Autoencoder (SSAE) Based IDS for Network Security von Kanimozhi, R., Neela Madheswari, A.

“… Ensuring robust security measures is imperative due to the substantial volume of network traffic …”
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Stacked Sparse Autoencoder-Based Deep Network for Fault Diagnosis of Rotating Machinery von Qi, Yumei, Shen, Changqing, Wang, Dong, Shi, Juanjuan, Jiang, Xingxing, Zhu, Zhongkui

“… Thus, a stacked sparse autoencoder (SAE)-based machine fault diagnosis method is proposed in this paper …”
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Combustion stability monitoring through flame imaging and stacked sparse autoencoder based deep neural network von Han, Zhezhe, Hossain, Md. Moinul, Wang, Yuwei, Li, Jian, Xu, Chuanlong

“… •A novel deep learning model is established for predicting combustion stability.•Automatic generation of combustion stability label is achieved.•Quantitative …”
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Research on Dung Beetle Optimization Based Stacked Sparse Autoencoder for Network Situation Element Extraction von Yang, Yongchao, Zhao, Pan

“… In existing studies, the stacked sparse autoencoder (SSAE) has been employed to extract features from unlabeled network flows …”
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Handling partially labeled network data: A semi-supervised approach using stacked sparse autoencoder von Aouedi, Ons, Piamrat, Kandaraj, Bagadthey, Dhruvjyoti

“… Network traffic analytics has become a crucial task in order to better understand and manage network resources, especially in the network softwarization era where the implementation of this concept …”
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Stacked sparse autoencoder networks and statistical shape models for automatic staging of distal femur trochlear dysplasia von Cerveri, Pietro, Belfatto, Antonella, Baroni, Guido, Manzotti, Alfonso

“… ), able to represent the individual morphology of the trochlea by means of a set of parameters and stacked sparse autoencoder (SSPA …”
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Hyperband Tuned Deep Neural Network With Well Posed Stacked Sparse AutoEncoder for Detection of DDoS Attacks in Cloud von Bhardwaj, Aanshi, Mangat, Veenu, Vig, Renu

“… Cloud computing has very attractive features like elastic, on demand and fully managed computer system resources and services. However, due to its distributed …”
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Stacked Sparse Autoencoder Modeling Using the Synergy of Airborne LiDAR and Satellite Optical and SAR Data to Map Forest Above-Ground Biomass von Shao, Zhenfeng, Zhang, Linjing, Wang, Lei

“… Timely, spatially complete, and reliable forest above-ground biomass (AGB) data are a prerequisite to support forest management and policy formulation …”
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Construction of a Sensitive and Speed Invariant Gearbox Fault Diagnosis Model Using an Incorporated Utilizing Adaptive Noise Control and a Stacked Sparse Autoencoder-Based Deep Neural Network von Nguyen, Cong Dai, Prosvirin, Alexander E., Kim, Cheol Hong, Kim, Jong-Myon

“… Gearbox fault diagnosis based on the analysis of vibration signals has been a major research topic for a few decades due to the advantages of vibration …”
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Deep Neural Network Hardware Implementation Based on Stacked Sparse Autoencoder von Coutinho, Maria G. F., Torquato, Matheus F., Fernandes, Marcelo A. C.

“… ) trained with the stacked sparse autoencoder (SSAE) technique. In order …”
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Tool wear monitoring for robotic milling based on multi-dimensional stacked sparse autoencoders and bidirectional LSTM networks with singularity features von Zhou, Chang’an, Zhang, Kaixing, Xu, Jiawei, Guo, Kai, Liu, Xin, Hu, Bingyin, Wang, Gang

“… The proposed tool wear monitoring method (TWM) relies on a sophisticated framework that integrates a multi-dimensional stacked sparse autoencoders (MD-SSAEs …”
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Deep Learning Based Retrieval of Forest Aboveground Biomass from Combined LiDAR and Landsat 8 Data von Zhang, Linjing, Shao, Zhenfeng, Liu, Jianchen, Cheng, Qimin

“… Estimation of forest aboveground biomass (AGB) is crucial for various technical and scientific applications, ranging from regional carbon and bioenergy …”
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