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检索条件"主题词=Sparse Auto-encoder"
79 条 记 录,以下是41-50 订阅
排序:
Turn-to-Turn Short Circuit of Motor Stator Fault Diagnosis Using Dropout Rate Improved Deep sparse autoencoder  3
Turn-to-Turn Short Circuit of Motor Stator Fault Diagnosis U...
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3rd IEEE Advanced Information Technology, Electronic and automation Control Conference (IAEAC)
作者: Wang, Botao Ma, Baohui Xu, Kexing Zheng, Tingting Xi An Jiao Tong Univ Sch Elect Engn Xian 710049 Shaanxi Peoples R China State Key Lab Large Elect Drive Syst & Equipment Tianshui 741020 Gansu Peoples R China
Motor is one of the most frequently used machines in industry. Ensuring the reliability of motor and timely identifying the fault type of motor can guarantee the properly working and prevent the great loss. In this pa... 详细信息
来源: 评论
Double Regularization-Based RVFL and edRVFL Networks for sparse-Dataset Classification  29th
Double Regularization-Based RVFL and edRVFL Networks for Spa...
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29th International Conference on Neural Information Processing
作者: Shi, Qiushi Suganthan, Ponnuthurai Nagaratnam Nanyang Technol Univ Sch Elect & Elect Engn 50 Nanyang Ave Singapore 639798 Singapore Qatar Univ Coll Engn KINDI Ctr Comp Res Doha Qatar
In our previous work, the random vector functional link network (RVFL) and the ensemble deep RVFL network (edRVFL) have been proven to be competitive for tabular-dataset classification, and their sparse pre-trained ve... 详细信息
来源: 评论
A FAULT DETECTION METHOD BASED ON STACKING THE SAE-SRBM FOR NONSTATIONARY AND STATIONARY HYBRID PROCESSES
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INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE 2021年 第1期31卷 29-43页
作者: Huang, Lei Ren, Hao Chai, Yi Qu, Jianfeng Huaiyin Normal Univ Sch Comp Sci & Technol Huaian City 223300 Jiangsu Peoples R China Chongqing Univ Sch Automat Chongqing 400044 Peoples R China Peng Cheng Lab Shenzhen 518000 Guangdong Peoples R China Minist Educ Key Lab Complex Syst Safety & Control Chongqing 400044 Peoples R China
This paper proposes a fault detection method by extracting nonlinear features for nonstationary and stationary hybrid industrial processes. The method is mainly built on the basis of a sparse auto-encoder and a sparse... 详细信息
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Subset based deep learning for RGB-D object recognition
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NEUROCOMPUTING 2015年 165卷 280-292页
作者: Bai, Jing Wu, Yan Zhang, Junming Chen, Fuqiang Tongji Univ Coll Elect & Informat Engn Shanghai 201804 Peoples R China
RGB-D camera can easily record both color and depth images and previous works have proved that combining them together could dramatically improve the RGB-D based object recognition accuracy. In this paper, a new metho... 详细信息
来源: 评论
Attitude data-based deep hybrid learning architecture for intelligent fault diagnosis of multi-joint industrial robots
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JOURNAL OF MANUFACTURING SYSTEMS 2021年 61卷 736-745页
作者: Long, Jianyu Mou, Jindong Zhang, Liangwei Zhang, Shaohui Li, Chuan Dongguan Univ Technol Sch Mech Engn Dongguan 523808 Peoples R China
Monitoring the transmission status of multi-joint industrial robots is very important for the accuracy of the robot motion. The fault diagnosis information is an indispensable basis for the collaborative maintenance o... 详细信息
来源: 评论
Online porosity prediction in laser welding of aluminum alloys based on a multi-fidelity deep learning framework
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JOURNAL OF INTELLIGENT MANUFACTURING 2024年 第1期35卷 55-73页
作者: Ma, Deyuan Jiang, Ping Shu, Leshi Gong, Zhaoliang Wang, Yilin Geng, Shaoning Huazhong Univ Sci & Technol Sch Mech Sci & Engn State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Hubei Peoples R China
Pore is one kind of the typical defects in aluminum alloys laser welding. Porosity is an important indicator for evaluating welding quality, and porosity assessment has attracted increasing attention. This paper prese... 详细信息
来源: 评论
Classification of medical images based on deep stacked patched auto-encoders
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MULTIMEDIA TOOLS AND APPLICATIONS 2020年 第35-36期79卷 25237-25257页
作者: Ben Ali, Ramzi Ejbali, Ridha Zaied, Mourad Univ Gabes ENIG Res Team Intelligent Machines RTIM Zrig 6029 Gabes Tunisia RTIM Gabes Tunisia
The concept of artificial intelligence is not new. Without going into details of the evolution of artificial intelligence, we can confess that recent techniques of deep neural networks have considerably relaunched the... 详细信息
来源: 评论
SVM or deep learning? A comparative study on remote sensing image classification
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SOFT COMPUTING 2017年 第23期21卷 7053-7065页
作者: Liu, Peng Choo, Kim-Kwang Raymond Wang, Lizhe Huang, Fang Chinese Acad Sci Inst Remote Sensing & Digital Earth 9 Dengzhuang South Rd Beijing 100094 Peoples R China China Univ Geosci Sch Comp Sci Wuhan 430074 Peoples R China Univ South Australia Sch Informat Technol & Math Sci Adelaide SA Australia Univ Elect Sci & Technol China Sch Resources & Environm Chengdu 611731 Sichuan Peoples R China
With constant advancements in remote sensing technologies resulting in higher image resolution, there is a corresponding need to be able to mine useful data and information from remote sensing images. In this paper, w... 详细信息
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Person-independent eye gaze prediction from eye images using patch-based features
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NEUROCOMPUTING 2016年 182卷 10-17页
作者: Lu, Feng Chen, Xiaowu Beihang Univ Sch Comp Sci & Engn Beijing 100191 Peoples R China Beihang Univ Int Res Inst Multidisciplinary Sci Beijing 100191 Peoples R China Beihang Univ Sch Comp Sci & Engn State Key Lab Virtual Real Technol & Syst Beijing 100191 Peoples R China
This paper delivers a preliminary attempt towards person-independent appearance-based gaze estimation. Conventional methods need to assume training and test data collected from the same person, otherwise eye shape dif... 详细信息
来源: 评论
Lossless-constraint Denoising based auto-encoders
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SIGNAL PROCESSING-IMAGE COMMUNICATION 2018年 63卷 92-99页
作者: Zhang, Jinsong Zhang, Yi Bai, Lianfa Han, Jing Nanjing Univ Sci & Technol Jiangsu Key Lab Spectral Imaging & Intelltgart Se Nanjing 210094 Jiangsu Peoples R China
In this paper, we address the poor generalization ability problem of tradidonal auto-encoder on noise data, and propose a Lossless-constraint Denoising (LD) method, which can enhance the anti-noise ability and robustn... 详细信息
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