Search Results - "Stacked sparse autoencoder"

Nondestructive evaluation of Zn content in rape leaves using MSSAE and hyperspectral imaging by Fu, Lvhui, Sun, Jun, Wang, Simin, Xu, Min, Yao, Kunshan, Zhou, Xin

“…[Display omitted] •Hyperspectral image applied for non-destructive detection of Zn content in plants.•An MSSAE was proposed for extracting deep features from…”
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Gearbox Fault Diagnosis Using a Deep Learning Model With Limited Data Sample by Saufi, Syahril Ramadhan, Ahmad, Zair Asrar Bin, Leong, Mohd Salman, Lim, Meng Hee

“…Massive volumes of data are needed for deep learning (DL) models to provide accurate diagnosis results. Numerous studies of fault diagnosis systems have…”
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Deep learning for polyp recognition in wireless capsule endoscopy images by Yuan, Yixuan, Meng, Max Q.‐H.

“…Purpose Wireless capsule endoscopy (WCE) enables physicians to examine the digestive tract without any surgical operations, at the cost of a large volume of…”
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Intelligent simultaneous fault diagnosis for solid oxide fuel cell system based on deep learning by Zhang, Zehan, Li, Shuanghong, Xiao, Yawen, Yang, Yupu

“…•An intelligent simultaneous fault diagnosis method is proposed for SOFC systems.•Stacked Sparse Autoencoder is used to solve simultaneous fault diagnosis…”
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Multi-objective data-ensemble wind speed forecasting model with stacked sparse autoencoder and adaptive decomposition-based error correction by Liu, Hui, Chen, Chao

“…•Extract the hidden representation of high-resolution wind speed data.•Ensemble base predictors trained by data with different resolutions.•Obtain combination…”
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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

“…Automated nuclear detection is a critical step for a number of computer assisted pathology related image analysis algorithms such as for automated grading of…”
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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.•Quantitative…”
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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

“…Deep learning has recently attracted significant attention in the field of hyperspectral images (HSIs) classification. However, the construction of an…”
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A Sleep Apnea Detection Method Based on Unsupervised Feature Learning and Single-Lead Electrocardiogram by Feng, Kaicheng, Qin, Hengji, Wu, Shan, Pan, Weifeng, Liu, Guanzheng

“…Sleep apnea (SA) is a harmful respiratory disorder that has caused widespread concern around the world. Considering that electrocardiogram (ECG)-based SA…”
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Unsupervised Spectral-Spatial Feature Learning With Stacked Sparse Autoencoder for Hyperspectral Imagery Classification by Tao, Chao, Pan, Hongbo, Li, Yansheng, Zou, Zhengrou

“…In this letter, different from traditional methods using original spectral features or handcraft spectral-spatial features, we propose to adaptively learn a…”
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Diagnosis of Interturn Short-Circuit Faults in Permanent Magnet Synchronous Motors Based on Few-Shot Learning Under a Federated Learning Framework by Zhang, Jinglin, Wang, Yanbo, Zhu, Kai, Zhang, Yi, Li, Yuanjiang

“…A large amount of labeled data are important to enhance the performance of deep-learning-based methods in the area of fault diagnosis. Because it is difficult…”
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Big data driven jobs remaining time prediction in discrete manufacturing system: a deep learning-based approach by Fang, Weiguang, Guo, Yu, Liao, Wenhe, Ramani, Karthik, Huang, Shaohua

“…Implementing advanced big data (BD) analytic is significant for successful incorporation of artificial intelligence in manufacturing. With the widespread…”
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Application of deep learning and near infrared spectroscopy in cereal analysis by Le, Ba Tuan

“…•A method for quickly analyzing cereal characteristics.•The method is based on deep learning and near infrared spectroscopy.•Uses stacked sparse autoencoder to…”
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Mask-based Self-supervised Network Intrusion Detection System by Lu, Xiaoya, Liu, Yifan, Feng, Fan, Liu, Yi, Liu, Zhenpeng

“…A significant number of network intrusion detection systems utilize unsupervised anomaly detection methodologies, the majority of which fail to account for the…”
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A Novel Order Analysis and Stacked Sparse Auto-Encoder Feature Learning Method for Milling Tool Wear Condition Monitoring by Ou, Jiayu, Li, Hongkun, Huang, Gangjin, Zhou, Qiang

“…Milling is a main processing mode of the modern manufacturing industry, which seriously affects the quality and precision of the machined workpiece. However,…”
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Nondestructive evaluation of bonding quality of dual-layer coatings based on the multi-feature ultrasonic method by Fan, Shaorui, Yuan, Maodan, Xu, Jianlin, Song, Yongfeng, Chen, Yan, Ji, Xuanrong

“…•A multi-feature ultrasonic (MFU) method was proposed to evaluate the bonding condition of dual-layer coatings.•Parametric numerical studies were carried out…”
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Brain Tumor Detection by Using Stacked Autoencoders in Deep Learning by Amin, Javaria, Sharif, Muhammad, Gul, Nadia, Raza, Mudassar, Anjum, Muhammad Almas, Nisar, Muhammad Wasif, Bukhari, Syed Ahmad Chan

“…Brain tumor detection depicts a tough job because of its shape, size and appearance variations. In this manuscript, a deep learning model is deployed to…”
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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

“…Combining deep learning (DL) and near-infrared (NIR) spectroscopy provides a new direction for revolutionizing agricultural quality assessment methods. Typical…”
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Infrared and Visible Image Fusion Based on Deep Decomposition Network and Saliency Analysis by Jian, Lihua, Rayhana, Rakiba, Ma, Ling, Wu, Shaowu, Liu, Zheng, Jiang, Huiqin

“…Traditional image fusion focuses on selecting an effective decomposition approach to extract representative features from the source image and attempts to find…”
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Deep Neural Network for Automatic Classification of Pathological Voice Signals by Chen, Lili, Chen, Junjiang

“…Computer-aided pathological voice detection is efficient for initial screening of pathological voice, and has received high academic and clinical attention…”
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