机构

• 自动化研究所 [6]
• 地理科学与资源研究所 [3]
• 计算技术研究所 [1]
• 海洋研究所 [1]
• 西安光学精密机械研究... [1]

采集方式

• OAI收割 [12]

内容类型

• 期刊论文 [10]
• 会议论文 [2]

发表日期

• 2024 [1]
• 2023 [1]
• 2022 [1]
• 2021 [2]
• 2020 [4]
• 2019 [1]
• 更多

学科主题

筛选

浏览/检索结果: 共12条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择提交时间升序提交时间降序发表日期升序发表日期降序题名升序题名降序作者升序作者降序 Sea Surface Temperature and Marine Heat Wave Predictions in the South China Sea: A 3D U-Net Deep Learning Model Integrating Multi-Source Data 期刊论文  OAI收割 ATMOSPHERE, 2024, 卷号: 15, 期号: 1, 页码: 20 作者:  Xie, Bowen;  Qi, Jifeng;  Yang, Shuguo;  Sun, Guimin;  Feng, Zhongkun   |  收藏  |  浏览/下载：17/0  |  提交时间：2024/04/07 sea surface temperature  deep learning  3D U-Net model  marine heat waves  South China Sea  multi-source data   A pixel-level deep segmentation network for automatic defect detection 期刊论文  OAI收割 EXPERT SYSTEMS WITH APPLICATIONS, 2023, 卷号: 215, 页码: 11 作者:  Yang, Lei;  Xu, Shuai;  Fan, Junfeng;  Li, En;  Liu, Yanhong   |  收藏  |  浏览/下载：21/0  |  提交时间：2023/02/22 Defect detection  Deep convolutional neural network  U-shape network  ConvLSTM network   An Automatic Deep Segmentation Network for Pixel-Level Welding Defect Detection 期刊论文  OAI收割 IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2022, 卷号: 71, 页码: 10 作者:  Yang, Lei;  Song, Shouan;  Fan, Junfeng;  Huo, Benyan;  Li, En   |  收藏  |  浏览/下载：33/0  |  提交时间：2022/06/06 Welding  Feature extraction  Image segmentation  Inspection  X-ray imaging  Manufacturing  Task analysis  Attention model  convolutional long short-term memory (ConvLSTM)  defect detection  feature fusion  hybrid loss  image segmentation   Generative Adversarial Capsule Network With ConvLSTM for Hyperspectral Image Classification 期刊论文  OAI收割 IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2021, 卷号: 18, 期号: 3, 页码: 523-527 作者:  Wang, Wei-Ye;  Li, Heng-Chao;  Deng, Yang-Jun;  Shao, Li-Yang;  Lu, Xiao-Qiang   |  收藏  |  浏览/下载：26/0  |  提交时间：2021/04/08 Capsule network (CapsNet)  convolutional neural network (CNN)  data augmentation  deep learning  generative adversarial network (GAN)  hyperspectral image (HSI) classification   Hybrid-Attention Enhanced Two-Stream Fusion Network for Video Venue Prediction 期刊论文  OAI收割 IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 卷号: 23, 页码: 2917-2929 作者:  Zhang, Yanchao;  Min, Weiqing;  Nie, Liqiang;  Jiang, Shuqiang   |  收藏  |  浏览/下载：48/0  |  提交时间：2021/12/01 Visualization  Feature extraction  Convolution  Streaming media  Object oriented modeling  Three-dimensional displays  Neural networks  Feature extraction  knowledge representation  supervised learning  video signal processing   A Framework to Predict High-Resolution Spatiotemporal PM(2.5)Distributions Using a Deep-Learning Model: A Case Study of Shijiazhuang, China 期刊论文  OAI收割 REMOTE SENSING, 2020, 卷号: 12, 期号: 17, 页码: 33 作者:  Zhang, Guangyuan;  Lu, Haiyue;  Dong, Jin;  Poslad, Stefan;  Li, Runkui   |  收藏  |  浏览/下载：18/0  |  提交时间：2021/03/16 PM2.5  AOD  XGBoost  prediction  deep learning  ConvLSTM  SARIMA   Temporally Identity-Aware SSD With Attentional LSTM 期刊论文  OAI收割 IEEE Transactions on Cybernetics, 2020, 卷号: 56, 期号: 6, 页码: 2674–2686 作者:  Xingyu Chen;  Junzhi Yu;  Zhengxing Wu;  Yu, Junzhi;  Chen, Xingyu   |  收藏  |  浏览/下载：22/0  |  提交时间：2020/06/08 Object detection  Sequential learning  Trackingby-detection  Video processing   The Prediction of Finely-Grained Spatiotemporal Relative Human Population Density Distributions in China 期刊论文  OAI收割 IEEE ACCESS, 2020, 卷号: 8, 页码: 181534-181546 作者:  Zheng, Zhi;  Zhang, Guangyuan   |  收藏  |  浏览/下载：10/0  |  提交时间：2021/03/16 Prediction  human population density distribution  SARIMA  ConvLSTM  Tencent positioning data  deep learning  geographic spatiotemporal big data   The Prediction of Finely-Grained Spatiotemporal Relative Human Population Density Distributions in China 期刊论文  OAI收割 IEEE ACCESS, 2020, 卷号: 8, 页码: 181534-181546 作者:  Zheng, Zhi;  Zhang, Guangyuan   |  收藏  |  浏览/下载：4/0  |  提交时间：2021/03/16 Prediction  human population density distribution  SARIMA  ConvLSTM  Tencent positioning data  deep learning  geographic spatiotemporal big data   Pixelwise Deep Sequence Learning for Moving Object Detection 期刊论文  OAI收割 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2019, 卷号: 29, 期号: 9, 页码: 2567-2579 作者:  Chen, Yingying;  Wang, Jinqiao;  Zhu, Bingke;  Tang, Ming;  Lu, Hanqing   |  收藏  |  浏览/下载：66/0  |  提交时间：2019/12/16 Moving object detection  background modeling  moving object proposal  convolutional neural networks