咨询与建议

限定检索结果

文献类型

  • 158 篇 期刊文献
  • 92 篇 会议
  • 2 篇 学位论文

馆藏范围

  • 252 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 235 篇 工学
    • 124 篇 计算机科学与技术...
    • 87 篇 电气工程
    • 40 篇 控制科学与工程
    • 33 篇 信息与通信工程
    • 24 篇 机械工程
    • 18 篇 软件工程
    • 15 篇 生物医学工程(可授...
    • 14 篇 仪器科学与技术
    • 12 篇 石油与天然气工程
    • 8 篇 材料科学与工程(可...
    • 8 篇 动力工程及工程热...
    • 8 篇 电子科学与技术(可...
    • 8 篇 测绘科学与技术
    • 5 篇 土木工程
    • 4 篇 化学工程与技术
    • 2 篇 建筑学
    • 2 篇 纺织科学与工程
    • 2 篇 农业工程
  • 47 篇 理学
    • 19 篇 生物学
    • 11 篇 物理学
    • 9 篇 化学
    • 8 篇 地球物理学
    • 4 篇 数学
    • 3 篇 地理学
    • 3 篇 系统科学
    • 2 篇 统计学(可授理学、...
  • 30 篇 医学
    • 13 篇 基础医学(可授医学...
    • 13 篇 临床医学
    • 3 篇 医学技术(可授医学...
  • 23 篇 管理学
    • 21 篇 管理科学与工程(可...
  • 8 篇 农学
  • 1 篇 法学
  • 1 篇 教育学

主题

  • 252 篇 sparse autoencod...
  • 63 篇 deep learning
  • 24 篇 fault diagnosis
  • 18 篇 feature extracti...
  • 16 篇 deep neural netw...
  • 11 篇 machine learning
  • 9 篇 dimensionality r...
  • 7 篇 support vector m...
  • 7 篇 deep belief netw...
  • 7 篇 convolutional ne...
  • 6 篇 image classifica...
  • 6 篇 feature selectio...
  • 6 篇 convolutional ne...
  • 6 篇 unsupervised lea...
  • 5 篇 compressed sensi...
  • 5 篇 anomaly detectio...
  • 5 篇 face recognition
  • 5 篇 autoencoder
  • 5 篇 unsupervised fea...
  • 5 篇 convolutional au...

机构

  • 6 篇 xian univ techno...
  • 6 篇 tianshui normal ...
  • 3 篇 nanyang technol ...
  • 2 篇 nanjing normal u...
  • 2 篇 zhongnan univ ec...
  • 2 篇 northeast petr u...
  • 2 篇 chinese acad sci...
  • 2 篇 hong kong univ s...
  • 2 篇 northeastern uni...
  • 2 篇 china univ petr ...
  • 2 篇 northwestern pol...
  • 2 篇 hebei univ affil...
  • 2 篇 kasetsart univ g...
  • 2 篇 ming chuan univ ...
  • 2 篇 hubei key lab ad...
  • 2 篇 shenzhen institu...
  • 2 篇 china univ geosc...
  • 2 篇 zhengzhou univ l...
  • 2 篇 natl cent univ d...
  • 2 篇 natl inst techno...

作者

  • 7 篇 xie guo
  • 7 篇 yang jing
  • 7 篇 yang yanxi
  • 3 篇 hu jun
  • 3 篇 nair madhu s.
  • 3 篇 zhang yu-dong
  • 3 篇 wang tianzhen
  • 3 篇 xin bin
  • 3 篇 wang shui-hua
  • 2 篇 zhu zhongkui
  • 2 篇 chen kunjin
  • 2 篇 li xin
  • 2 篇 wu min
  • 2 篇 shen changqing
  • 2 篇 kim ji-seon
  • 2 篇 liu ming
  • 2 篇 liu hongyi
  • 2 篇 lin feng
  • 2 篇 hou xiao-xia
  • 2 篇 hou zengguang

语言

  • 242 篇 英文
  • 5 篇 中文
  • 4 篇 其他
  • 1 篇 法文
检索条件"主题词=sparse AutoEncoder"
252 条 记 录,以下是231-240 订阅
排序:
A Deep Learning and Softmax Regression Fault Diagnosis Method for Multi-Level Converter
A Deep Learning and Softmax Regression Fault Diagnosis Metho...
收藏 引用
IEEE International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives
作者: Bin Xin Tianhao Tang Tianzhen Wang Shanghai Maritime University Shanghai China
With the single-tube and double-tube fault of seven-level converter, this paper presents a new way to learn the faults feature based on the deep neural network of sparse autoencoder. sparse autoencoder is an unsupervi... 详细信息
来源: 评论
Evaluating Shape Representations for Maya Glyph Classification
收藏 引用
ACM JOURNAL ON COMPUTING AND CULTURAL HERITAGE 2016年 第3期9卷 14-14页
作者: Can, Gulcan Odobez, Jean-Marc Gatica-Perez, Daniel Idiap Res Inst Martigny Switzerland Ecole Polytech Fed Lausanne Lausanne Switzerland Idiap Res Inst Ctr Parc Rue Marconi 19 CH-1920 Martigny Switzerland
Shape representations are critical for visual analysis of cultural heritage materials. This article studies two types of shape representations in a bag-of-words-based pipeline to recognize Maya glyphs. The first is a ... 详细信息
来源: 评论
Fine-grained representation learning in convolutional autoencoders
收藏 引用
JOURNAL OF ELECTRONIC IMAGING 2016年 第2期25卷 023018-023018页
作者: Luo, Chang Wang, Jie Air Force Engn Univ Air & Missile Def Coll 1 East Changle Rd Xian 710051 CN Peoples R China
Convolutional autoencoders (CAEs) have been widely used as unsupervised feature extractors for high-resolution images. As a key component in CAEs, pooling is a biologically inspired operation to achieve scale and shif... 详细信息
来源: 评论
A sparse FEATURE REPRESENTATION FOR GENETIC DATA ANALYSIS  14
A SPARSE FEATURE REPRESENTATION FOR GENETIC DATA ANALYSIS
收藏 引用
International Conference on Machine Learning and Cybernetics (ICMLC)
作者: Liu, Hua-Hao Huang, Pei-Jie Lin, Pi-Yuan Lin, Wen-Hu Qi, Pei-Heng Song, Chong-Hua South China Agr Univ Coll Math & Informat Guangzhou 510642 Guangdong Peoples R China
Feature representation is one of the key research issues in machine learning. In some applications with high dimensionality of data, e.g. genomic microarray data, obtaining a good feature representation with effective... 详细信息
来源: 评论
Fuzzy Rule Reduction using sparse Auto-Encoders
Fuzzy Rule Reduction using Sparse Auto-Encoders
收藏 引用
IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
作者: Sevakula, Rahul K. Verma, Nishchal K. Indian Inst Technol Kanpur Dept Elect Engn Kanpur Uttar Pradesh India
Fuzzy Rule based regression, classification and control have found great use in modern applications due to its simplicity, flexibility and capability. A key issue in all such methods is the computation time. Computati... 详细信息
来源: 评论
The effect of whitening transformation on pooling operations in convolutional autoencoders
收藏 引用
EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING 2015年 第1期2015卷 1页
作者: Li, Zuhe Fan, Yangyu Liu, Weihua Northwestern Polytech Univ Sch Elect & Informat Xian 710072 Peoples R China Zhengzhou Univ Light Ind Sch Comp & Commun Engn Zhengzhou 450002 Peoples R China
Convolutional autoencoders (CAEs) are unsupervised feature extractors for high-resolution images. In the pre-processing step, whitening transformation has widely been adopted to remove redundancy by making adjacent pi... 详细信息
来源: 评论
Convolutional autoencoder-based Color Image Classification using Chroma Subsampling in YCbCr Space  8
Convolutional Autoencoder-based Color Image Classification u...
收藏 引用
Proceedings 2015 8 International Congress on Image and Signal Processing (CISP)
作者: Li, Zuhe Fan, Yangyu Wang, Fengqin Northwestern Polytech Univ Sch Elect & Informat Xian Peoples R China Zhengzhou Univ Light Ind Sch Comp & Commun Engn Zhengzhou Peoples R China
We propose a convolutional autoencoder neural network for image classification in YCbCr color space to reduce computational complexity. We first learned local image features from image patches in YCbCr space with a sp... 详细信息
来源: 评论
Abnormal Event Detection using Recurrent Neural Network
Abnormal Event Detection using Recurrent Neural Network
收藏 引用
2nd International Conference on Computer Science and Applications (CSA)
作者: Zhou, Xu-gang Zhang, Li-qing Shanghai Jiao Tong Univ Dept Comp Sci Shanghai Peoples R China
In this paper, we introduce a simple but novel model to detect abnormal event in surveillance video using sparse autoencoder and recurrent neuron network. In this model, we first train a sparse autoencoder to extract ... 详细信息
来源: 评论
A Vehicle Type Recognition Method based on sparse Auto Encoder
A Vehicle Type Recognition Method based on Sparse Auto Encod...
收藏 引用
2015 International Conference on Computer Information Systems and Industrial Applications(CISIA2015)
作者: H.L.Rong Y.X.Xia Wu Han University of Technology
In recent years,feature learning methods based on unsupervised learning get more and more *** now,Unsupervised feature learning has been applied to solve many problems such as detection,recognition and *** this paper,... 详细信息
来源: 评论
Fuzzy Rule Reduction using sparse Auto-Encoders
Fuzzy Rule Reduction using Sparse Auto-Encoders
收藏 引用
IEEE International Conference on Fuzzy Systems
作者: Rahul K. Sevakula Nishchal K. Verma Department of Electrical Engineering Indian Institute of Technology Kanpur
Fuzzy Rule based regression, classification and control have found great use in modern applications due to its simplicity, flexibility and capability. A key issue in all such methods is the computation time. Computati... 详细信息
来源: 评论