Search Results - Stacked sparse autoencoder data construction*

Cost Prediction of Tunnel Construction Based on Interpretative Structural Model and Stacked Sparse Autoencoder by Zhou, Jing-Qun, Liu, Qi-Ming, Ma, Chang-Xi, Li, Dong

“… Recently, the machine learning technique offers an accurate and efficient method for forecasting construction expenses, introducing a novel approach to cost accounting other than conventional calculation techniques…”
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Building Extraction Based on an Optimized Stacked Sparse Autoencoder of Structure and Training Samples Using LIDAR DSM and Optical Images by Yan, Yiming, Tan, Zhichao, Su, Nan, Zhao, Chunhui

“…In this paper, a building extraction method is proposed based on a stacked sparse autoencoder with an optimized structure and training samples…”
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Rock mass type prediction for tunnel boring machine using a novel semi-supervised method by Yu, Honggan, Tao, Jianfeng, Qin, Chengjin, Xiao, Dengyu, Sun, Hao, Liu, Chengliang

“…•A set of data preprocessing methods is proposed for the cleaning of the big machine data…”
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An automatic and integrated self-diagnosing system for the silting disease of drainage pipelines based on SSAE-TSNE and MS-LSTM by Di, Danyang, Wang, Dianchang, Fang, Hongyuan, He, Qiang, Zhou, Lifen, Chen, Xianming, Sun, Bin, Zhang, Jinping

“…•Siltation diagnosing systems of drainage pipes cannot achieve full coverage.•Generative adversarial network solves the small data sample problem…”
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Research on Deep Adaptive Clustering Method Based on Stacked Sparse Autoencoders for Concrete Truck Mixers Driving Conditions by Huang, Ying, Jiang, Fachao, Xie, Haiming

“… Then, stacked sparse autoencoders (SSAE) are employed to extract deep features from normalized driving data…”
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Stacked sparse autoencoder networks and statistical shape models for automatic staging of distal femur trochlear dysplasia by 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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Enhancing breast cancer classification using a deep sparse wavelet autoencoder approach by Alzakari, Sarah A., Hassairi, Salima, Hussan, Amel Ali Al, Ejbali, Ridha

“…). The key innovation of our method lies in its construction: DSWAE combines stacked wavelet autoencoders to create a robust model specifically designed for differentiating between distinct categories in 2D breast cancer image datasets…”
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Active Transfer Learning Network: A Unified Deep Joint Spectral-Spatial Feature Learning Model for Hyperspectral Image Classification by Deng, Cheng, Xue, Yumeng, Liu, Xianglong, Li, Chao, Tao, Dacheng

“… More specifically, deep joint spectral-spatial feature is first extracted through hierarchical stacked sparse autoencoder (SSAE) networks…”
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scIAE: an integrative autoencoder-based ensemble classification framework for single-cell RNA-seq data by Yin, Qingyang, Wang, Yang, Guan, Jinting, Ji, Guoli

“… Since single-cell gene expression data are high-dimensional and sparse with dropouts, we propose scIAE, an integrative autoencoder-based ensemble classification framework, to firstly perform multiple…”
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A novel modulation classification method in cognitive radios using higher-order cumulants and denoising stacked sparse autoencoder by Xu Zhu, Fujii, Takeo

“… We use Stacked Denoising Sparse Autoencoder as a classifier for single-carrier modulation classification…”
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A Distributed Anomaly Detection Method of Operation Energy Consumption Using Smart Meter Data by Ye Yuan, Kebin Jia

“… An IOT-based distributed structure is implemented to execute data interaction. Stacked sparse autoencoder is used to extract the high-level representation from massive monitoring data acquired automatically from actual smart meter network…”
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Health Status Assessment of Diesel Engine Valve Clearance Based on BFA-BOA-VMD Adaptive Noise Reduction and Multi-Channel Information Fusion by Liu, Yangshuo, Kang, Jianshe, Wen, Liang, Bai, Yunjie, Guo, Chiming

“…Regarding the problem of the valve gap health status being difficult to assess due to the complex composition of the condition monitoring signal during the…”
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Deep Learning Role in Early Diagnosis of Prostate Cancer by Reda, Islam, Khalil, Ashraf, Elmogy, Mohammed, Abou El-Fetouh, Ahmed, Shalaby, Ahmed, Abou El-Ghar, Mohamed, Elmaghraby, Adel, Ghazal, Mohammed, El-Baz, Ayman

“… of those apparent diffusion coefficients using a generalized Gaussian Markov random field model. Then, construction of the cumulative…”
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Improving the second-tier classification of methylmalonic acidemia patients using a machine learning ensemble method by Zhu, Zhi-Xing, Genchev, Georgi Z., Wang, Yan-Min, Ji, Wei, Ren, Yong-Yong, Tian, Guo-Li, Sriswasdi, Sira, Lu, Hui

“… We utilized mass spectrometry-based features consisting of 11 amino acids and 31 carnitines derived from dried blood samples of neonatal patients, followed by additional ratio feature construction…”
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A Deep Transfer NOx Emission Inversion Model of Diesel Vehicles with Multisource External Influence by Xu, Zhenyi, Wang, Ruibin, Kang, Yu, Zhang, Yujun, Xia, Xiushan, Wang, Renjun

“…By installing on-board diagnostics (OBD) on tested vehicles, the after-treatment exhaust emissions can be monitored in real time to construct driving cycle-based emission models, which can provide data support for the construction…”
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Active Transfer Learning Network: A Unified Deep Joint Spectral-Spatial Feature Learning Model For Hyperspectral Image Classification by Deng, Cheng, Xue, Yumeng, Liu, Xianglong, Li, Chao, Tao, Dacheng

“… More specifically, deep joint spectral-spatial feature is first extracted through hierarchical stacked sparse autoencoder (SSAE) networks…”
Get full text