中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
计算技术研究所 [4]
数学与系统科学研究院 [2]
自动化研究所 [2]
力学研究所 [1]
重庆绿色智能技术研究... [1]
合肥物质科学研究院 [1]
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OAI收割 [12]
内容类型
期刊论文 [12]
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2025 [2]
2023 [2]
2022 [3]
2019 [1]
2018 [1]
2017 [1]
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computer s... [1]
computer s... [1]
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SPMGAE: Self-purified masked graph autoencoders release robust expression power
期刊论文
OAI收割
NEUROCOMPUTING, 2025, 卷号: 611, 页码: 14
作者:
Song, Shuhan
;
Li, Ping
;
Dun, Ming
;
Zhang, Yuan
;
Cao, Huawei
  |  
收藏
  |  
浏览/下载:52/0
  |  
提交时间:2024/12/06
Graph neural networks
Masked graph autoencoders
Robustness
Graph adversarial attacks
EfficientSTNet: A Deep Learning Approach for Multi-Class DDoS Detection
期刊论文
OAI收割
IEEE ACCESS, 2025, 卷号: 13, 页码: 157587-157599
作者:
Zhang, Lei
;
Bai, Yujuan
;
Xue, Tao
;
Feng GH(冯冠华)
;
Zhang, Haibin
  |  
收藏
  |  
浏览/下载:15/0
  |  
提交时间:2025/10/27
Feature extraction
Denial-of-service attack
Computer crime
Entropy
Deep learning
Accuracy
Floods
Telecommunication traffic
Computational modeling
Autoencoders
DDoS
DDoS attack detection
convolutional neural network
deep learning
self-attention mechanism
Flood Disaster Assessment Method Based on a Stacked Denoising Autoencoder
期刊论文
OAI收割
ELECTRONICS, 2023, 卷号: 12
作者:
Chen, Yanping
;
Wang, Yilun
;
Wu, Zhize
;
Zou, Le
;
Li, Wenbo
  |  
收藏
  |  
浏览/下载:60/0
  |  
提交时间:2023/11/10
flood disaster
stacked denoising autoencoders
deep learning
DiamondNet: A Neural-Network-Based Heterogeneous Sensor Attentive Fusion for Human Activity Recognition
期刊论文
OAI收割
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 页码: 11
作者:
Zhu, Yida
;
Luo, Haiyong
;
Chen, Runze
;
Zhao, Fang
  |  
收藏
  |  
浏览/下载:41/0
  |  
提交时间:2023/12/04
Convolutional denoising autoencoders (CDAEs)
global-attention mechanism
graph convolutional networks
human activity recognition (HAR)
multisensor modality
self-attention mechanism
Variational deep embedding-based active learning for the diagnosis of pneumonia
期刊论文
OAI收割
FRONTIERS IN NEUROROBOTICS, 2022, 卷号: 16, 页码: 7
作者:
Huang, Jian
;
Ding, Wen
;
Zhang, Jiarun
;
Li, Zhao
;
Shu, Ting
  |  
收藏
  |  
浏览/下载:63/0
  |  
提交时间:2023/02/07
pneumonia diagnosis
active learning
variational autoencoders
brain-like computing
human-centric computing
A novel deep learning approach for tourism volume forecasting with tourist search data
期刊论文
OAI收割
INTERNATIONAL JOURNAL OF TOURISM RESEARCH, 2022, 页码: 15
作者:
Li, Mingchen
;
Zhang, Chengyuan
;
Sun, Shaolong
;
Wang, Shouyang
  |  
收藏
  |  
浏览/下载:44/0
  |  
提交时间:2023/02/07
bi-directional gated recurrent unit
search engine data
stacked autoencoders
tourism volume forecasting
Plausible 3D Face Wrinkle Generation Using Variational Autoencoders
期刊论文
OAI收割
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2022, 卷号: 28, 期号: 9, 页码: 3113-3125
作者:
Deng, Qixin
;
Ma, Luming
;
Jin, Aobo
;
Bi, Huikun
;
Le, Binh Huy
  |  
收藏
  |  
浏览/下载:45/0
  |  
提交时间:2022/12/07
Faces
Three-dimensional displays
Solid modeling
Shape
Computational modeling
Pipelines
Data models
Face modeling
wrinkle synthesis
deep generative models
variational autoencoders
DCCR: Deep Collaborative Conjunctive Recommender for Rating Prediction
期刊论文
OAI收割
IEEE ACCESS, 2019, 卷号: 7, 页码: 60186-60198
作者:
Wang, Qingxian
;
Peng, Binbin
;
Shi, Xiaoyu
;
Shang, Tianqi
;
Shang, Mingsheng
  |  
收藏
  |  
浏览/下载:112/0
  |  
提交时间:2019/06/24
Recommender systems
collaborative filtering
rating prediction
denoising autoencoders
multi layered perceptron
Research of stacked denoising sparse autoencoder
期刊论文
OAI收割
NEURAL COMPUTING & APPLICATIONS, 2018, 卷号: 30, 期号: 7, 页码: 2083-2100
作者:
Meng, Lingheng
;
Ding, Shifei
;
Zhang, Nan
;
Zhang, Jian
  |  
收藏
  |  
浏览/下载:54/0
  |  
提交时间:2019/12/10
Autoencoder
Stacked autoencoders
Feature extraction
Unsupervised learning
Sparse coding
Deep learning
Building Energy Consumption Prediction: An Extreme Deep Learning Approach
期刊论文
OAI收割
ENERGIES, 2017, 卷号: 10, 期号: 10, 页码: 1-20
作者:
Li, Chengdong
;
Ding, Zixiang
;
Zhao, Dongbin
;
Yi, Jianqiang
;
Zhang, Guiqing
  |  
收藏
  |  
浏览/下载:67/0
  |  
提交时间:2017/12/30
Building Energy Consumption
Deep Learning
Stacked Autoencoders
Extreme Learning Machine