咨询与建议

限定检索结果

文献类型

  • 2,538 篇 期刊文献
  • 1,649 篇 会议
  • 51 篇 学位论文
  • 2 册 图书
  • 1 篇 资讯

馆藏范围

  • 4,241 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 3,885 篇 工学
    • 2,431 篇 计算机科学与技术...
    • 1,572 篇 电气工程
    • 682 篇 信息与通信工程
    • 419 篇 控制科学与工程
    • 382 篇 软件工程
    • 263 篇 仪器科学与技术
    • 162 篇 生物医学工程(可授...
    • 161 篇 机械工程
    • 152 篇 测绘科学与技术
    • 142 篇 电子科学与技术(可...
    • 93 篇 石油与天然气工程
    • 76 篇 环境科学与工程(可...
    • 71 篇 动力工程及工程热...
    • 70 篇 交通运输工程
    • 65 篇 材料科学与工程(可...
    • 63 篇 网络空间安全
    • 62 篇 土木工程
    • 58 篇 化学工程与技术
    • 40 篇 生物工程
    • 34 篇 力学(可授工学、理...
  • 855 篇 理学
    • 283 篇 物理学
    • 244 篇 生物学
    • 149 篇 化学
    • 138 篇 地球物理学
    • 127 篇 数学
  • 539 篇 医学
    • 340 篇 临床医学
    • 121 篇 基础医学(可授医学...
    • 83 篇 特种医学
  • 366 篇 管理学
    • 308 篇 管理科学与工程(可...
    • 37 篇 图书情报与档案管...
  • 75 篇 农学
  • 21 篇 经济学
  • 19 篇 法学
  • 14 篇 艺术学
  • 13 篇 文学
  • 11 篇 教育学
  • 3 篇 哲学
  • 1 篇 军事学

主题

  • 4,241 篇 autoencoder
  • 1,037 篇 deep learning
  • 427 篇 anomaly detectio...
  • 364 篇 machine learning
  • 232 篇 feature extracti...
  • 155 篇 convolutional ne...
  • 152 篇 unsupervised lea...
  • 151 篇 neural network
  • 128 篇 neural networks
  • 108 篇 lstm
  • 105 篇 classification
  • 104 篇 training
  • 103 篇 dimensionality r...
  • 82 篇 cnn
  • 78 篇 representation l...
  • 78 篇 clustering
  • 77 篇 deep neural netw...
  • 76 篇 transfer learnin...
  • 75 篇 decoding
  • 67 篇 convolutional ne...

机构

  • 16 篇 univ chinese aca...
  • 10 篇 cent south univ ...
  • 10 篇 univ elect sci &...
  • 9 篇 chongqing univ c...
  • 9 篇 univ chinese aca...
  • 9 篇 northwestern pol...
  • 9 篇 iiit delhi new d...
  • 9 篇 nanyang technol ...
  • 8 篇 hong kong polyte...
  • 8 篇 cent south univ ...
  • 8 篇 tianjin univ col...
  • 8 篇 univ elect sci &...
  • 8 篇 korea adv inst s...
  • 8 篇 peng cheng lab p...
  • 7 篇 china univ geosc...
  • 7 篇 chinese acad sci...
  • 7 篇 harbin engn univ...
  • 7 篇 brno university ...
  • 6 篇 queens univ dept...
  • 6 篇 new jersey inst ...

作者

  • 20 篇 majumdar angshul
  • 13 篇 wang wei
  • 7 篇 zhang lin
  • 7 篇 zhang lei
  • 7 篇 wang jian
  • 7 篇 wang hao
  • 7 篇 liu li
  • 7 篇 li bin
  • 7 篇 kim jin-young
  • 7 篇 hoydis jakob
  • 7 篇 gao lianru
  • 7 篇 zhang wei
  • 7 篇 guo lei
  • 6 篇 wang lei
  • 6 篇 li li
  • 6 篇 wang kai
  • 6 篇 li yuan
  • 6 篇 liu jie
  • 6 篇 zhou mengchu
  • 6 篇 li xiang

语言

  • 4,072 篇 英文
  • 109 篇 其他
  • 33 篇 中文
  • 7 篇 法文
  • 6 篇 德文
  • 6 篇 土耳其文
  • 2 篇 朝鲜文
  • 1 篇 西班牙文
  • 1 篇 意大利文
  • 1 篇 日文
  • 1 篇 葡萄牙文
检索条件"主题词=autoencoder"
4241 条 记 录,以下是321-330 订阅
排序:
Synthesizing Talking Faces from Text and Audio: An autoencoder and Sequence-to-Sequence Convolutional Neural Network
收藏 引用
PATTERN RECOGNITION 2020年 第0期102卷 107231-000页
作者: Liu, Na Zhou, Tao Ji, Yunfeng Zhao, Ziyi Wan, Lihong Univ Shanghai Sci & Technol Inst Machine Intelligence Shanghai Peoples R China Incept Inst Artificial Intelligence Abu Dhabi U Arab Emirates Shanghai Jiao Tong Univ Inst Image Proc & Pattern Recognit Dept Automat Shanghai Peoples R China Netease Inc Hangzhou Peoples R China
Synthesizing talking face from text and audio is increasingly becoming a direction in human-machine and face-to-face interactions. Although progress has been made, several existing methods either have unsatisfactory c... 详细信息
来源: 评论
RODEO: Robust DE-aliasing autoencoder for real-time medical image reconstruction
收藏 引用
PATTERN RECOGNITION 2017年 63卷 499-510页
作者: Mehta, Janki Majumdar, Angshul Indraprastha Inst Informat Technol New Delhi India
In this work we address the problem of real-time dynamic medical (MRI and X-Ray CT) image reconstruction from parsimonious samples (Fourier frequency space for MRI and sinogram/tomographic projections for CT). Today t... 详细信息
来源: 评论
Ontology construction and mapping of multi-source heterogeneous data based on hybrid neural network and autoencoder
收藏 引用
NEURAL COMPUTING & APPLICATIONS 2023年 第36期35卷 25131-25141页
作者: Zhao, Wenbin Fu, Zijian Fan, Tongrang Wang, Jiaqi Shijiazhuang Tiedao Univ Sch Informat Sci & Technol Shijiazhuang Hebei Peoples R China
In big data era, multi-source heterogeneous data become the biggest obstacle to data sharing due to its high dimension and inconsistent structure. Using text classification to solve the ontology construction and mappi... 详细信息
来源: 评论
Estimation of missing air pollutant data using a spatiotemporal convolutional autoencoder (May, 10.1007/s00521-022-07224-2, 2022)
收藏 引用
NEURAL COMPUTING & APPLICATIONS 2022年 第18期34卷 16155-16155页
作者: Wardana, I. Nyoman Kusuma Gardner, Julian W. Fahmy, Suhaib A. Univ Warwick Sch Engn Coventry CV4 7AL W Midlands England King Abdullah Univ Sci & Technol KAUST Comp Elect & Math Sci & Engn Thuwal 23955 Saudi Arabia Politekn Negeri Bali Dept Elect Engn Bali 80364 Indonesia
A key challenge in building machine learning models for time series prediction is the incompleteness of the datasets. Missing data can arise for a variety of reasons, including sensor failure and n... 详细信息
来源: 评论
Dual-attention LSTM autoencoder for fault detection in industrial complex dynamic processes
收藏 引用
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION 2024年 185卷 1145-1159页
作者: Zeng, Lei Jin, Qiwen Lin, Zhiming Zheng, Chenghang Wu, Yingchun Wu, Xuecheng Gao, Xiang Zhejiang Univ State Key Lab Clean Energy Utilizat Hangzhou 310027 Peoples R China Zhejiang Univ Key Lab Clean Energy & Carbon Neutral Zhejiang Pro Hangzhou 310027 Peoples R China
Complex dynamic characteristics resulting from multi-system coupling and closed-loop control are ubiquitous in modern industrial process data, presenting significant challenges for process fault detection. However, co... 详细信息
来源: 评论
TSMAE: A Novel Anomaly Detection Approach for Internet of Things Time Series Data Using Memory-Augmented autoencoder
收藏 引用
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2023年 第5期10卷 2978-2990页
作者: Gao, Honghao Qiu, Binyang Barroso, Ramon J. Duran Hussain, Walayat Xu, Yueshen Wang, Xinheng Shanghai Univ Sch Comp Engn & Sci Shanghai 200444 Peoples R China Univ Valladolid Fac Telecommun Engn Valladolid 47002 Spain Victoria Univ Business Sch Melbourne Vic 3011 Australia Univ Technol Sydney Ultimo NSW 2007 Australia Xidian Univ Sch Comp Sci & Technol Xian 710126 Peoples R China Xian Jiaotong Liverpool Univ Sch Adv Technol Suzhou 215123 Peoples R China
With the development of communication, the Internet of Things (IoT) has been widely deployed and used in industrial manufacturing, intelligent transportation, and healthcare systems. The time-series feature of the IoT... 详细信息
来源: 评论
A Suspicious Financial Transaction Detection Model Using autoencoder and Risk-Based Approach
收藏 引用
IEEE ACCESS 2024年 12卷 68926-68939页
作者: Koo, Kyungmo Park, Minyoung Yoon, Byungun Sch Engn Dept Fintech & Blockchain Seoul 100715 South Korea Dongguk Univ Dept Ind & Syst Engn Seoul 04620 South Korea
This study focuses on the detection of suspicious transactions characterized by the opaque and complex electronic channels that have emerged with the advancement of electronic financial technology. A model that can im... 详细信息
来源: 评论
Discriminative autoencoder for Feature Extraction: Application to Character Recognition
收藏 引用
NEURAL PROCESSING LETTERS 2019年 第3期49卷 1723-1735页
作者: Gogna, Anupriya Majumdar, Angshul Indraprastha Inst Informat Technol New Delhi India
Conventionally, autoencoders are unsupervised representation learning tools. In this work, we propose a novel discriminative autoencoder. Use of supervised discriminative learning ensures that the learned representati... 详细信息
来源: 评论
Detecting spatiotemporal irregularities in videos via a 3D convolutional autoencoder
收藏 引用
JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2020年 67卷 102747-102747页
作者: Yan, Mengjia Meng, Jingjing Zhou, Chunluan Tu, Zhigang Tan, Yap-Peng Yuan, Junsong Nanyang Technol Univ Sch Elect & Elect Engn 50 Nanyang Ave Singapore 639798 Singapore SUNY Buffalo Comp Sci & Engn Dept Buffalo NY USA Wuhan Univ State Key Lab Informat Engn Surveying Mapping & R Ruoyu Rd 129 Wuhan Peoples R China
Spatiotemporal irregularities (i.e., the uncommon appearance and motion patterns) in videos are difficult to detect, as they are usually not well defined and appear rarely in videos. We tackle this problem by learning... 详细信息
来源: 评论
RffAe-S: autoencoder Based on Random Fourier Feature With Separable Loss for Unsupervised Signal Modulation Clustering
收藏 引用
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2022年 第11期18卷 7910-7919页
作者: Bai, Jing Wang, Yiran Xiao, Zhu Alazab, Mamoun Xidian Univ Sch Artificial Intelligence Key Lab Intelligent Percept & Image Understanding Minist Educ Xian 710071 Peoples R China Guangdong Lab Artificial Intelligence & Digital E Shenzhen 518060 Peoples R China Hunan Univ Coll Comp Sci & Elect Engn Changsha 410082 Peoples R China Charles Darwin Univ Casuarina NT 0811 Australia
Unsupervised signal modulation clustering is becoming increasingly important due to its application in the dynamic spectrum access process of 5G wireless communication and threat detection at the physical layer of Int... 详细信息
来源: 评论