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131-140 订阅
排序:
Out-of-Roundness Wheel Damage Identification in Railway Vehicles Using autoencoder Models
收藏 引用
APPLIED SCIENCES-BASEL 2025年 第5期15卷 2662-2662页
作者: Melo, Renato Finotti, Rafaelle Guedes, Antonio Goncalves, Vitor Meixedo, Andreia Ribeiro, Diogo Barbosa, Flavio Cury, Alexandre Univ Fed Juiz de Fora Grad Program Civil Engn BR-36036900 Juiz De Fora Brazil Univ Porto Fac Engn CONSTRUCT LESE P-4200465 Porto Portugal Polytech Porto Sch Engn CONSTRUCT LESE P-4200465 Porto Portugal
This study presents a comparative analysis of three autoencoder (AE) models-Variational autoencoder (VAE), sparse autoencoder (SAE), and Convolutional autoencoder (CAE)-to detect and quantify structural anomalies in r... 详细信息
来源: 评论
A multilevel recovery diagnosis model for rolling bearing faults from imbalanced and partially missing monitoring data
收藏 引用
MATHEMATICAL BIOSCIENCES AND ENGINEERING 2023年 第3期20卷 5223-5242页
作者: Yang, Jing Xie, Guo Yang, Yanxi Li, Qijun Yang, Cheng Tianshui Normal Univ Sch Mechatron & Automot Engn Tianshui 741000 Peoples R China Xian Univ Technol Sch Automat & Informat Engn Xian 710048 Peoples R China
As an indispensable part of large Computer Numerical Control machine tool, rolling bearing faults diagnosis is particularly important. However, due to the imbalanced distribution and partially missing of collected mon... 详细信息
来源: 评论
Learning-Based Cuckoo Search Algorithm to Schedule a Flexible Job Shop With Sequencing Flexibility
收藏 引用
IEEE TRANSACTIONS ON CYBERNETICS 2023年 第10期53卷 6663-6675页
作者: Lin, ChengRan Cao, ZhengCai Zhou, MengChu Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing 100029 Peoples R China Zhejiang Gongshang Univ Sch Informat & Elect Engn Hangzhou 310018 Peoples R China New Jersey Inst Technol Helen & John C Hartmann Dept Elect & Comp Engn Newark NJ 07102 USA
This work considers an extended version of flexible job-shop problem from a postprinting or semiconductor manufacturing environment, which needs a directed acyclic graph rather than a linear order to describe the prec... 详细信息
来源: 评论
An Effective sparse autoencoders based Deep Learning Framework for fMRI Scans Classification  22
An Effective Sparse Autoencoders based Deep Learning Framewo...
收藏 引用
22nd International Conference on Enterprise Information Systems (ICEIS)
作者: Mahmoud, Abeer M. Karamti, Hanen Alrowais, Fadwa Ain Shams Univ Fac Comp & Informat Sci Cairo Egypt Princess Nourah bint Abdulrahman Univ Coll Comp & Informat Sci Comp Sci Dept POB 84428 Riyadh Saudi Arabia Univ Sfax MIRACL Lab ISIMS BP 242 Sfax 3021 Tunisia
Deep Learning (DL) identifies features of medical scans automatically in a way very near to expert doctors and sometimes over beats in treatment procedures. In fact, it increases model generalization as it doesn't... 详细信息
来源: 评论
A random deep neural system for heartbeat classification
收藏 引用
EVOLVING SYSTEMS 2023年 第1期14卷 37-48页
作者: Siouda, Roguia Nemissi, Mohamed Seridi, Hamid Univ 8 Mai 1945 Dept Comp Sci LabSTIC Lab PB 401 Guelma Algeria Univ 8 Mai 1945 Dept Elect & Telecommun LabSTIC Lab PB 401 Guelma Algeria
This paper introduces a heartbeat classification system that combines three types of neural networks: random neural networks, deep autoencoders and RBF neural networks. The aim is to make use of the advantages of thes... 详细信息
来源: 评论
Heart disease risk prediction using deep learning techniques with feature augmentation
收藏 引用
MULTIMEDIA TOOLS AND APPLICATIONS 2023年 第20期82卷 31759-31773页
作者: Teresa Garcia-Ordas, Maria Bayon-Gutierrez, Martin Benavides, Carmen Aveleira-Mata, Jose Alberto Benitez-Andrades, Jose Univ Leon Escuela Ingn Ind & Informat SECOMUCI Res Grp Campus Vegazana s-n Leon 24071 Leon Spain Univ Leon Dept Elect Syst & Automat Engn SALBIS Res Grp Campus Vegazana s-n Leon 24071 Leon Spain
Cardiovascular diseases state as one of the greatest risks of death for the general population. Late detection in heart diseases highly conditions the chances of survival for patients. Age, sex, cholesterol level, sug... 详细信息
来源: 评论
A novel adaptive fault diagnosis algorithm for multi-machine equipment: application in bearing and diesel engine
收藏 引用
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL 2023年 第3期22卷 1677-1707页
作者: Liu, Yangshuo Kang, Jianshe Bai, Yunjie Guo, Chiming Army Engn Univ PLA Shijiazhuang 050003 Hebei Peoples R China Chinese Peoples Liberat Army Unit 66029 Xilinguolemeng Peoples R China
This paper proposes an adaptive fault diagnosis algorithm based on vibration signals for fault diagnosis of bearings and diesel engines. First, the improved nonlinear gray wolf optimization algorithm (NGWO) is adopted... 详细信息
来源: 评论
STACKED sparse autoencoder (SSAE) BASED FRAMEWORK FOR NUCLEI PATCH CLASSIFICATION ON BREAST CANCER HISTOPATHOLOGY  11
STACKED SPARSE AUTOENCODER (SSAE) BASED FRAMEWORK FOR NUCLEI...
收藏 引用
11th IEEE International Symposium on Biomedical Imaging (ISBI)
作者: Xu, Jun Xiang, Lei Hang, Renlong Wu, Jianzhong Nanjing Univ Informat Sci & Technol Nanjing 210044 Jiangsu Peoples R China Jiangsu Canc Hosp Nanjing 210000 Jiangsu Peoples R China
In this paper, a Stacked sparse autoencoder (SSAE) based framework is presented for nuclei classification on breast cancer histopathology. SSAE works very well in learning useful high-level feature for better represen... 详细信息
来源: 评论
SV-SAE: Layer-Wise Pruning for autoencoder Based on Link Contributions
收藏 引用
IEEE ACCESS 2025年 13卷 75666-75678页
作者: Rheey, Joohong Park, Hyunggon Ewha Womans Univ Dept Elect & Elect Engn Seoul 03760 South Korea
autoencoders are a type of deep neural network and are widely used for unsupervised learning, particularly in tasks that require feature extraction and dimensionality reduction. While most research focuses on compress... 详细信息
来源: 评论
sparse auto encoder driven support vector regression based deep learning model for predicting network intrusions
收藏 引用
PEER-TO-PEER NETWORKING AND APPLICATIONS 2021年 第4期14卷 2419-2429页
作者: Preethi, D. Khare, Neelu Vellore Inst Technol Sch Informat Technol & Engn Vellore Tamil Nadu India
The Network Intrusion Detection System (NIDS) assumes a prominent aspect in ensuring network security. It serves better than traditional network security mechanisms, such as firewall systems. The result of the NIDS in... 详细信息
来源: 评论