Search Results - deep stacked sparse autoencoder

Secondary Pulmonary Tuberculosis Identification Via pseudo-Zernike Moment and Deep Stacked Sparse Autoencoder: Secondary Pulmonary Tuberculosis Identification Via pseudo-Zernike Moment and Deep Stacked Sparse Autoencoder by Wang, Shui-Hua, Satapathy, Suresh Chandra, Zhou, Qinghua, Zhang, Xin, Zhang, Yu-Dong

“…) as the feature extractor and deep stacked sparse autoencoder (DSSAE) as the classifier. In addition, 18-way data augmentation is employed to avoid overfitting…”
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Predicting protein-protein interactions from protein sequences by a stacked sparse autoencoder deep neural network by 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 Stacked Sparse Autoencoders – A Breast Cancer Classifier by Munir, Muhammad Asif, Aslam, Muhammad Aqeel, Shafique, Muhammad, Ahmed, Rauf, Mehmood, Zafar

“… In this article, Deep Stacked Sparse Autoencoders for breast cancer diagnostic and classification are proposed…”
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Reliable Fault Diagnosis of Rotary Machine Bearings Using a Stacked Sparse Autoencoder-Based Deep Neural Network by Sohaib, Muhammad, Kim, Jong-Myon

“… In this study, using complex envelope spectra and stacked sparse autoencoder…”
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Breath analysis based early gastric cancer classification from deep stacked sparse autoencoder neural network by 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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Combustion stability monitoring through flame imaging and stacked sparse autoencoder based deep neural network by 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…”
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Pseudo Zernike Moment and Deep Stacked Sparse Autoencoder for COVID-19 Diagnosis by Zhang, Yu-Dong, Attique Khan, Muhammad, Zhu, Ziquan, Wang, Shui-Hua

“… Afterward, we use a deep-stacked sparse autoencoder (DSSAE) as the classifier. Besides, multiple-way data augmentation is chosen to overcome overfitting…”
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Fast identification of maize varieties with small samples using near-infrared spectral feature selection and improved stacked sparse autoencoder deep learning by Yang, Dongfeng, Hu, Jun

“… For this reason, this paper combines NIR spectral feature selection with improved stacked sparse autoencoder (ISSAE…”
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Deep network approach with stacked sparse autoencoders in detection of DDoS attacks on SDN-based VANET by 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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Stacked Sparse Autoencoder-Based Deep Network for Fault Diagnosis of Rotating Machinery by 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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Predicting Protein Interactions Using a Deep Learning Method-Stacked Sparse Autoencoder Combined with a Probabilistic Classification Vector Machine by Jiang, Tonghai, Zhang, Libo, Zhou, Xi, Cheng, Li, Li, Liping, You, Zhuhong, Wang, Yanbin, Li, Xiao

“… This method was developed based on a deep learning algorithm-stacked sparse autoencoder (SSAE) combined with a Legendre moment…”
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Five-category classification of pathological brain images based on deep stacked sparse autoencoder by Jia, Wenjuan, Muhammad, Khan, Wang, Shui-Hua, Zhang, Yu-Dong

“… Then, we used deep stacked sparse autoencoder with minibatch scaled conjugate gradient to train the network, and the softmax…”
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Face recognition via Deep Stacked Denoising Sparse Autoencoders (DSDSA) by Görgel, Pelin, Simsek, Ahmet

“… In this paper, the proposed face recognition system namely Deep Stacked Denoising Sparse Autoencoders (DSDSA…”
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K-Means Clustering Optimizing Deep Stacked Sparse Autoencoder by Bi, Yandong, Wang, Peng, Guo, Xuchao, Wang, Zhijun, Cheng, Shuhan

“… How to speed up training is a problem deserving of study. In order to accelerate training, K-means clustering optimizing deep stacked sparse autoencoder (K-means sparse SAE…”
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Optimal Deep Stacked Sparse Autoencoder Based Osteosarcoma Detection and Classification Model by Fakieh, Bahjat, AL-Ghamdi, Abdullah S. AL-Malaise, Ragab, Mahmoud

“…Osteosarcoma is a kind of bone cancer which generally starts to develop in the lengthy bones in the legs and arms. Because of an increase in occurrence of…”
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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 by 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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Single stuck-at-faults detection using test generation vector and deep stacked-sparse-autoencoder by Malihi, Leila, Malihi, Razieh

“… This data-based method detects hundreds of single stuck-at faults in the ALU circuits, utilizing deep stacked-sparse-autoencoder (SSAE…”
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A Hybrid Method of Enhancing Accuracy of Facial Recognition System Using Gabor Filter and Stacked Sparse Autoencoders Deep Neural Network by Jaber, Abdullah Ghanim, Muniyandi, Ravie Chandren, Usman, Opeyemi Lateef, Singh, Harprith Kaur Rajinder

“…Face recognition has grown in popularity due to the ease with which most recognition systems can find and recognize human faces in images and videos. However,…”
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A deep learning framework with hybrid stacked sparse autoencoder for type 2 diabetes prediction by Abdussamad, Daud, Hanita, Sokkalingam, Rajalingam, Zubair, Muhammad, Khan, Iliyas Karim, Mahmood, Zafar

“… To overcome this challenge, this study introduces a deep learning-based algorithm, Hybrid Stacked Sparse Autoencoder (HSSAE…”
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Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images by Jun Xu, Lei Xiang, Qingshan Liu, Gilmore, Hannah, Jianzhong Wu, Jinghai Tang, Madabhushi, Anant

“…) the variability in size, shape, appearance, and texture of the individual nuclei. Recently there has been interest in the application of "Deep Learning" strategies for classification and analysis of big image data…”
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