Výsledky vyhledávání - Sparse Denoising Autoencoder*

Hyperspectral image classification using k-sparse denoising autoencoder and spectral–restricted spatial characteristics Autor Lan, Rushi, Li, Zeya, Liu, Zhenbing, Gu, Tianlong, Luo, Xiaonan

“… This paper proposes a novel k-sparse denoising autoencoder (KDAE) with a softmax classifier for HSI classification…”
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Denoising Sparse Autoencoder-Based Ictal EEG Classification Autor Qiu, Yang, Zhou, Weidong, Yu, Nana, Du, Peidong

“… This paper presents an EEG classification framework based on the denoising sparse autoencoder…”
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Electricity theft detection based on stacked sparse denoising autoencoder Autor Huang, Yifan, Xu, Qifeng

“…Inspired by the powerful feature extraction and the data reconstruction ability of autoencoder, a stacked sparse denoising autoencoder is developed for electricity theft detection in this paper…”
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Stacked pruning sparse denoising autoencoder based intelligent fault diagnosis of rolling bearings Autor Zhu, Haiping, Cheng, Jiaxin, Zhang, Cong, Wu, Jun, Shao, Xinyu

“…This paper proposes a new stacked pruning sparse denoising autoencoder (sPSDAE) model for intelligent fault diagnosis of rolling bearings…”
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A novel multimodal framework for automatic recognition of individual cattle based on hybrid features using sparse stacked denoising autoencoder and group sparse representation techniques Autor Kumar, Santosh, Kumar, Sunil, Shafi, Mehak, Chaube, Mithilesh Kumar

“… This paper proposes an automatic recognition system to identify cattle based on face and muzzle image features using sparse Stacked Denoising Autoencoder (SDAE…”
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Research on denoising sparse autoencoder Autor Meng, Lingheng, Ding, Shifei, Xue, Yu

“… In order to extract useful features, meanwhile improve robustness and overcome overfitting, we studied denoising sparse autoencoder through adding corrupting operation and sparsity constraint to traditional autoencoder…”
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Toward Robust Fault Identification of Complex Industrial Processes Using Stacked Sparse-Denoising Autoencoder With Softmax Classifier Autor Liu, Jinping, Xu, Longcheng, Xie, Yongfang, Ma, Tianyu, Wang, Jie, Tang, Zhaohui, Gui, Weihua, Yin, Huazhan, Jahanshahi, Hadi

“…This article proposes a robust end-to-end deep learning-induced fault recognition scheme by stacking multiple sparse-denoising autoencoders with a Softmax classifier, called stacked spare-denoising autoencoder (SSDAE…”
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Low-dose CT restoration via stacked sparse denoising autoencoders Autor Liu, Yan, Zhang, Yi

“… Stacked sparse denoising autoencoders, which were designed originally for training noisy samples, are adopted to construct the architecture…”
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Towards robust and understandable fault detection and diagnosis using denoising sparse autoencoder and smooth integrated gradients Autor Peng, Peng, Zhang, Yi, Wang, Hongwei, Zhang, Heming

“… In this paper, a two-step robust and understandable fault detection and diagnosis framework is developed to address this challenge by exploiting denoising sparse autoencoder and smooth integrated gradients…”
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Face recognition via Deep Stacked Denoising Sparse Autoencoders (DSDSA) Autor Görgel, Pelin, Simsek, Ahmet

“… In this paper, the proposed face recognition system namely Deep Stacked Denoising Sparse Autoencoders (DSDSA…”
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Classification model of electricity consumption behavior based on sparse denoising autoencoder feature dimensionality reduction and spectral clustering Autor Huang, Yifan, Yao, Zhengnan, Xu, Qifeng

“…•A classification model of electricity consumption based on sparse denoising autoencoder and spectral clustering is proposed…”
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Research of stacked denoising sparse autoencoder Autor Meng, Lingheng, Ding, Shifei, Zhang, Nan, Zhang, Jian

“… In order to present data more efficiently and study how to express data through deep networks, we propose a novel stacked denoising sparse autoencoder in this paper…”
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A stacked convolutional sparse denoising autoencoder model for underwater heterogeneous information data Autor Wang, Xingmei, Zhao, Yixu, Teng, Xuyang, Sun, Weiqi

“…•A novel stacked convolutional sparse denoising autoencoder (SCSDA) model is proposed.•The unrelated dataset was developed to simulate the underwater heterogeneous information data as the training set…”
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Early fault detection method for nuclear power plants based on sparse denoising autoencoder and kernel principal component analysis Autor Yin, Wenzhe, Xia, Hong, Huang, Xueying, Shan, Longfei, Ran, Wenhao, Jia, Zhujun

“…). To accurately identify early faults in NPPs, this study proposes a novel fault detection method based on sparse denoising autoencoder (SDAE…”
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Modified metaheuristics with stacked sparse denoising autoencoder model for cervical cancer classification Autor Vaiyapuri, Thavavel, Alaskar, Haya, Syed, Liyakathunisa, Aljohani, Eman, Alkhayyat, Ahmed, Shankar, K., Kumar, Sachin

“…•Present an optimal SSDAE to classify cervical cancer on pap smear images.•Employ Kapur's entropy segmentation and efficientnet feature extraction.•Propose…”
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Decoding whole-genome mutational signatures in 37 human pan-cancers by denoising sparse autoencoder neural network Autor Pei, Guangsheng, Hu, Ruifeng, Dai, Yulin, Zhao, Zhongming, Jia, Peilin

“…Millions of somatic mutations have recently been discovered in cancer genomes. These mutations in cancer genomes occur due to internal and external mutagenesis…”
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Low-level structure feature extraction for image processing via stacked sparse denoising autoencoder Autor Fan, Zunlin, Bi, Duyan, He, Linyuan, Shiping, Ma, Gao, Shan, Li, Cheng

“… In this paper, we propose a novel low-level structure feature extraction for image processing based on deep neural network, stacked sparse denoising autoencoder (SSDA…”
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Dynamic video anomaly detection and localization using sparse denoising autoencoders Autor Narasimhan, Medhini G., S., Sowmya Kamath

“… A unique sparse denoising autoencoder architecture is used, that significantly reduced…”
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Flatness pattern recognition based on stacked sparse denoising autoencoder and improved Osprey optimisation algorithm kernel-extreme learning machine Autor Zhou, Yaluo, Zhang, Shaochuan, Liu, Wenguang, Zhang, Ruicheng

“… proposes a flatness recognition method based on stack sparse denoising autoencoder (SSDAE) with improved Osprey optimisation algorithm kernel-extreme learning machine…”
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A sparse stacked denoising autoencoder with optimized transfer learning applied to the fault diagnosis of rolling bearings Autor Sun, Meidi, Wang, Hui, Liu, Ping, Huang, Shoudao, Fan, Peng

“…•Fault diagnosis by stacked autoencoder requires less professional knowledge.•Domain adaptation by optimized transfer learning reduces the algorithm’s complexity…”
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