Search Results - "stacked denoising autoencoder neural network"

Traffic Image Analysis Based on Stacked Denoising Autoencoder Neural Network by Kim, Daehyon

“…This study aims to explore major neural network models - Stacked Denoising Autoencoder (SDAE), Deep Belief Network (DBN), Backpropagation - that have recently…”
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An imbalanced data classification algorithm of improved autoencoder neural network by Chenggang Zhang, Wei Gao, Jiazhi Song, Jinqing Jiang

“… Pointing to the overfitting and noise problems of oversampling algorithm when synthesizing new minority class samples, the current study proposed a stacked denoising autoencoder neural network (SDAE…”
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Application of VIS/NIR Spectroscopy and SDAE-NN Algorithm for Predicting the Cold Storage Time of Salmon by Wu, Ting, Yang, Ling, Zhong, Nan

“… Meanwhile, a double-layer stacked denoising autoencoder neural network (SDAE-NN) algorithm was introduced to establish the prediction model without spectral pre-preprocessing…”
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Identifying marsh dieback events from Landsat image series (1998-2018) with an Autoencoder in the NIWB estuary, South Carolina by Li, Huixuan, Wang, Cuizhen, Ellis, Jean T., Cui, Yuxin, Miller, Gwen, Morris, James T.

“… A Stacked Denoising Autoencoder neural network was developed to identify the NDVI anomalies on the trajectories…”
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Stacked Denoising Autoencoders Applied to Star/Galaxy Classification by Hao-ran, Qin, Ji-ming, Lin, Jun-yi, Wang

“…) data, we introduced the new deep learning algorithm, namely the SDA (stacked denoising autoencoder…”
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Satellite Observations and Spatiotemporal Assessment of Salt Marsh Dieback along Coastal South Carolina (1990–2019) by Li, Huixuan

“…Coastal wetland mapping is often difficult because of the heterogeneous vegetation compositions and associated tidal effects. Past studies in the Gulf/Atlantic…”
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Adaptive Centre-Weighted Oversampling for Class Imbalance in Software Defect Prediction by Zha, Qi, Yan, Xuefeng, Zhou, Yong

“…In the field of software engineering, software defect prediction can maintain the high quality of software products, which is a popular current research topic…”
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Indoor Motion State Recognition using Denoising Autoencoders on Smartphone by Dai, H., Tao, C. B., Lu, Y., Lu, H. B.

“… In a second place, this paper managed to go through a stacked denoising autoencoder neural network, resulting in an output layer with seven different indoor movement states…”
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