咨询与建议

限定检索结果

文献类型

  • 45 篇 期刊文献
  • 34 篇 会议

馆藏范围

  • 79 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 74 篇 工学
    • 47 篇 计算机科学与技术...
    • 26 篇 电气工程
    • 16 篇 控制科学与工程
    • 10 篇 信息与通信工程
    • 7 篇 机械工程
    • 6 篇 仪器科学与技术
    • 5 篇 软件工程
    • 3 篇 电子科学与技术(可...
    • 1 篇 力学(可授工学、理...
    • 1 篇 光学工程
    • 1 篇 材料科学与工程(可...
    • 1 篇 土木工程
    • 1 篇 化学工程与技术
    • 1 篇 生物医学工程(可授...
    • 1 篇 网络空间安全
  • 15 篇 管理学
    • 13 篇 管理科学与工程(可...
    • 2 篇 图书情报与档案管...
  • 11 篇 理学
    • 5 篇 数学
    • 4 篇 生物学
    • 2 篇 物理学
    • 2 篇 系统科学
    • 2 篇 统计学(可授理学、...
    • 1 篇 化学
    • 1 篇 生态学
  • 3 篇 医学
    • 2 篇 基础医学(可授医学...
    • 1 篇 临床医学
  • 1 篇 文学
    • 1 篇 外国语言文学
  • 1 篇 农学

主题

  • 79 篇 sparse auto-enco...
  • 17 篇 deep learning
  • 9 篇 fault diagnosis
  • 7 篇 feature extracti...
  • 6 篇 feature learning
  • 4 篇 transfer learnin...
  • 4 篇 deep neural netw...
  • 3 篇 compressed sensi...
  • 3 篇 svm
  • 3 篇 machine learning
  • 3 篇 classification
  • 3 篇 feature selectio...
  • 2 篇 intrusion detect...
  • 2 篇 structural healt...
  • 2 篇 gated recurrent ...
  • 2 篇 rolling bearing
  • 2 篇 offline text-ind...
  • 2 篇 support vector m...
  • 2 篇 auto-encoder
  • 2 篇 soft-max classif...

机构

  • 2 篇 tongji univ coll...
  • 2 篇 dongguan univ te...
  • 2 篇 sun yat sen univ...
  • 1 篇 nanyang technol ...
  • 1 篇 shiraz univ sch ...
  • 1 篇 leiden univ leid...
  • 1 篇 chinese acad sci...
  • 1 篇 east china univ ...
  • 1 篇 southwest jiaoto...
  • 1 篇 xiamen univ fuji...
  • 1 篇 dalian univ tech...
  • 1 篇 univ brasilia pr...
  • 1 篇 school of inform...
  • 1 篇 sichuan jingyi a...
  • 1 篇 southeast univ s...
  • 1 篇 chinese acad sci...
  • 1 篇 xi an jiao tong ...
  • 1 篇 univ sfax natl e...
  • 1 篇 school of commun...
  • 1 篇 minzu univ china...

作者

  • 2 篇 bai jing
  • 2 篇 wang wei
  • 2 篇 cury alexandre a...
  • 2 篇 long jianyu
  • 2 篇 lai jianhuang
  • 2 篇 barbosa flavio d...
  • 2 篇 zhang yi
  • 2 篇 finotti rafaelle...
  • 2 篇 wu yan
  • 1 篇 e tang
  • 1 篇 liu shangdong
  • 1 篇 huang fang
  • 1 篇 lv zheng
  • 1 篇 liu dong
  • 1 篇 chaolin zhang
  • 1 篇 guo yingqing
  • 1 篇 yang ran
  • 1 篇 li baoqing
  • 1 篇 she daoming
  • 1 篇 kumar bhardwaj a...

语言

  • 75 篇 英文
  • 2 篇 其他
  • 2 篇 中文
检索条件"主题词=Sparse Auto-encoder"
79 条 记 录,以下是21-30 订阅
排序:
Deep neural network for halftone image classification based on sparse auto-encoder
收藏 引用
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2016年 50卷 245-255页
作者: Zhang, Yan Zhang, Erhu Chen, Wanjun Xian Univ Technol Fac Mech & Precis Instrumental Engn Xian 710048 Peoples R China Armed Police Acad Dept Border Control & Immigrat Langfang 065000 Peoples R China Xian Univ Technol Fac Printing Packing Engn & Digital Media Technol Xian 710048 Peoples R China
To restore high quality continuous tone images from each class of halftone images, halftone image fine classification is the key problem. In this paper, a novel feature learning method is proposed for classifying 14 k... 详细信息
来源: 评论
A sparse auto-encoder-based deep neural network approach for induction motor faults classification
收藏 引用
MEASUREMENT 2016年 89卷 171-178页
作者: Sun, Wenjun Shao, Siyu Zhao, Rui Yan, Ruqiang Zhang, Xingwu Chen, Xuefeng Southeast Univ Sch Instrument Sci & Engn Nanjing 210096 Jiangsu Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Nanyang Ave Singapore 639798 Singapore Xi An Jiao Tong Univ Collaborat Innovat Ctr High End Mfg Equipment Xian 710049 Peoples R China
This paper presents a deep neural network (DNN) approach for induction motor fault diagnosis. The approach utilizes sparse auto-encoder (SAE) to learn features, which belongs to unsupervised feature learning that only... 详细信息
来源: 评论
Layerwise feature selection in Stacked sparse auto-encoder for tumor type prediction
Layerwise feature selection in Stacked Sparse Auto-Encoder f...
收藏 引用
IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM)
作者: Singh, Vikas Baranwal, Nikhil Sevakula, Rahul K. Verma, Nishchal K. Cui, Yan Indian Inst Technol Kanpur Dept Elect Engn Kanpur Uttar Pradesh India Indian Inst Technol Kanpur Fac Elect Engn Kanpur Uttar Pradesh India Univ Tennessee Hlth Sci Ctr Fac Microbiol Immunol & Biochem Knoxville TN 37996 USA
Transcriptome data has been proved to be very valuable for clinical applications, such as diagnosis and prognosis of various cancers. In this paper, we present layer-wise feature selection in conjunction with stacked ... 详细信息
来源: 评论
Deep Representations Based on sparse auto-encoder Networks for Face Spoofing Detection  11th
Deep Representations Based on Sparse Auto-Encoder Networks f...
收藏 引用
11th Chinese Conference on Biometric Recognition (CCBR)
作者: Yang, Dakun Lai, Jianhuang Mei, Ling Sun Yat Sen Univ Sch Data & Comp Sci Guangzhou 510006 Guangdong Peoples R China
automatic face recognition plays significant role in biometrics systems, and face spoofing has raised concerns at the same time, since a photo or video of an authorized uesr's face could be used for deceiving the ... 详细信息
来源: 评论
sparse auto-encoder based feature learning for human body detection in depth image
收藏 引用
SIGNAL PROCESSING 2015年 112卷 43-52页
作者: Su, Song-Zhi Liu, Zhi-Hui Xu, Su-Ping Li, Shao-Zi Ji, Rongrong Xiamen Univ Sch Informat Sci & Technol Xiamen 361005 Peoples R China Xiamen Univ Fujian Key Lab Brain Like Intelligent Syst Xiamen 361005 Peoples R China
Human body detection in depth image is an active research topic in computer vision. But depth feature extraction is still an open problem. In this paper, a novel feature learning method based on sparse auto-encoder (S... 详细信息
来源: 评论
Locality-Constrained sparse auto-encoder for Image Classification
收藏 引用
IEEE SIGNAL PROCESSING LETTERS 2015年 第8期22卷 1070-1073页
作者: Luo, Wei Yang, Jian Xu, Wei Fu, Tao Nanjing Univ Sci & Technol Sch Comp Sci & Engn Nanjing 210094 Jiangsu Peoples R China
We propose a locality-constrained sparse auto-encoder (LSAE) for image classification in this letter. Previous work has shown that the locality is more essential than sparsity for classification task. We here introduc... 详细信息
来源: 评论
A novel method of diagnosing premature ventricular contraction based on sparse auto-encoder and softmax regression
收藏 引用
BIO-MEDICAL MATERIALS AND ENGINEERING 2015年 第Sup1期26卷 S1549-S1558页
作者: Yang, Jianli Bai, Yang Li, Guojun Liu, Ming Liu, Xiuling Hebei Univ Coll Elect & Informat Engn Key Lab Digital Med Engn Hebei Prov Baoding 071000 Hebei Peoples R China
Premature ventricular contraction (PVC) is one of the most serious arrhythmias. Without early diagnosis and proper treatment, PVC can result in significant complications. In this paper, a novel feature extraction meth... 详细信息
来源: 评论
Large data density peak clustering based on sparse autoencoder and data space meshing via evidence probability distribution
收藏 引用
EAI ENDORSED TRANSACTIONS ON SCALABLE INFORMATION SYSTEMS 2025年 第1期12卷 1-15页
作者: Lu, Fang Harbin Finance Univ Harbin 150000 Peoples R China
The development of big data analysis technology has brought new development opportunities to the production and management of various industries. Through the mining and analysis of various data in the operation proces... 详细信息
来源: 评论
License Plate Detection Based On sparse auto-encoder  8
License Plate Detection Based On Sparse Auto-Encoder
收藏 引用
8th International Symposium on Computational Intelligence and Design (ISCID)
作者: Yang, Ran Yin, Huarui Chen, Xiaohui Univ Sci & Technol China Dept Elect Engn & Informat Sci Hefei Peoples R China
In modern society, automatic license plate recognition (ALPR) plays an important role in the field of Intelligent Transport Systems (ITS). In order to recognize the license plate efficiently, the location of the licen... 详细信息
来源: 评论
Novelty Detection Using sparse auto-encoders to Characterize Structural Vibration Responses
收藏 引用
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2022年 第10期47卷 13049-13062页
作者: Finotti, Rafaelle Piazzaroli Barbosa, Flavio de Souza Cury, Alexandre Abrahao Pimentel, Roberto Leal Univ Fed Juiz de Fora Grad Program Computat Modeling Juiz De Fora Brazil Univ Fed Juiz de Fora Grad Program Civil Engn Juiz De Fora Brazil Univ Fed Paraiba Grad Program Civil & Environm Engn Joao Pessoa Paraiba Brazil
Deep learning techniques have been increasingly popular for detecting structural novelties in recent years. The deep learning notion originates from the theory of neural networks, and it comprises several machine lear... 详细信息
来源: 评论