机构

• 自动化研究所 [7]
• 长春光学精密机械与物... [2]
• 计算技术研究所 [1]
• 沈阳自动化研究所 [1]

采集方式

• OAI收割 [11]

内容类型

• 期刊论文 [9]
• 会议论文 [2]

发表日期

• 2023 [1]
• 2022 [3]
• 2021 [3]
• 2020 [1]
• 2010 [1]
• 2009 [1]
• 更多

学科主题

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浏览/检索结果: 共11条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Contour Primitive of Interest Extraction Network Based on Dual-Metric One-Shot Learning for Vision Measurement 期刊论文  OAI收割 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2023, 卷号: 19, 期号: 4, 页码: 5839-5848 作者:  Qin, Fangbo;  Lin, Shan;  Xu, De   |  收藏  |  浏览/下载：14/0  |  提交时间：2023/11/17 Feature extraction  Measurement  Task analysis  Imaging  Image segmentation  Prototypes  Training  Contour extraction  deep learning  metric learning  one-shot learning  vision measurement   Adaptively Weighted k-Tuple Metric Network for Kinship Verification 期刊论文  OAI收割 IEEE TRANSACTIONS ON CYBERNETICS, 2022, 页码: 14 作者:  Huang, Sheng;  Lin, Jingkai;  Huangfu, Luwen;  Xing, Yun;  Hu, Junlin   |  收藏  |  浏览/下载：32/0  |  提交时间：2022/06/10 Measurement  Feature extraction  Task analysis  Faces  Deep learning  Convolutional neural networks  Genetics  Deep learning  kinship verification  metric learning  relation network (RN)  triplet loss   Evolving Metric Learning for Incremental and Decremental Features 期刊论文  OAI收割 IEEE Transactions on Circuits and Systems for Video Technology, 2022, 卷号: 32, 期号: 4, 页码: 2290-2302 作者:  Dong JH(董家华);  Cong Y(丛杨);  Sun G(孙干);  Zhang T(张涛);  Tang X(唐旭)   |  收藏  |  浏览/下载：73/0  |  提交时间：2021/08/28 Data models  Extraterrestrial measurements  Feature extraction  instance and feature evolutions  low-rank constraint  Measurement  Online metric learning  Optimization  Robot sensing systems  smoothed Wasserstein distance  Task analysis   Adversarial-Metric Learning for Audio-Visual Cross-Modal Matching 期刊论文  OAI收割 IEEE TRANSACTIONS ON MULTIMEDIA, 2022, 卷号: 24, 页码: 338-351 作者:  Zheng, Aihua;  Hu, Menglan;  Jiang, Bo;  Huang, Yan;  Yan, Yan   |  收藏  |  浏览/下载：37/0  |  提交时间：2022/03/17 Visualization  Task analysis  Measurement  Speech recognition  Videos  Location awareness  Image recognition  Adversarial learning  audio-visual matching  cross-modal learning  metric learning   PRDP: Person Reidentification With Dirty and Poor Data 期刊论文  OAI收割 IEEE TRANSACTIONS ON CYBERNETICS, 2021, 页码: 13 作者:  Xu, Furong;  Ma, Bingpeng;  Chang, Hong;  Shan, Shiguang   |  收藏  |  浏览/下载：28/0  |  提交时间：2022/06/21 Training  Noise measurement  Data models  Task analysis  Training data  Predictive models  Heuristic algorithms  Dirty  metric learning  person reidentification (ReID)  poor   Question-Guided Erasing-Based Spatiotemporal Attention Learning for Video Question Answering 期刊论文  OAI收割 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 13 作者:  Liu, Fei;  Liu, Jing;  Hong, Richang;  Lu, Hanqing   |  收藏  |  浏览/下载：30/0  |  提交时间：2022/01/27 Spatiotemporal phenomena  Measurement  Visualization  Knowledge discovery  Task analysis  Cognition  Semantics  Erasing mechanism  metric learning  spatiotemporal attention  video question answering (VideoQA)   Adaptive Deep Metric Learning for Affective Image Retrieval and Classification 期刊论文  OAI收割 IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 卷号: 23, 页码: 1640-1653 作者:  Yao, Xingxu;  She, Dongyu;  Zhang, Haiwei;  Yang, Jufeng;  Cheng, Ming-Ming   |  收藏  |  浏览/下载：26/0  |  提交时间：2021/08/15 Measurement  Visualization  Semantics  Feature extraction  Task analysis  Image analysis  Image retrieval  Affective image retrieval  convolutional neural network  deep metric learning  visual sentiment analysis   Learning to Align via Wasserstein for Person Re-Identification 期刊论文  OAI收割 IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 页码: 7104-7116 作者:  Zhang, Zhizhong;  Xie, Yuan;  Li, Ding;  Zhang, Wensheng;  Tian, Qi   |  收藏  |  浏览/下载：30/0  |  提交时间：2020/08/03 Semantics  Heating systems  Measurement  Learning systems  Training  Estimation  Feature extraction  Person re-identification  deep metric learning  convolutional neural network  Wasserstein distance   Animated models coarsening with local area distortion and deformation degree control (EI CONFERENCE) 会议论文  OAI收割 International Conference on Image Processing and Pattern Recognition in Industrial Engineering, August 7, 2010 - August 8, 2010, Xi'an, China 作者:  Zhang S.;  Zhao J. 收藏  |  浏览/下载：23/0  |  提交时间：2013/03/25 In computer graphics applications  mesh coarsening is an important technique to alleviate the workload of visualization processing. Compared to the extensive works on static model approximation  very little attentions have been paid to animated models. In this paper  we propose a new method to approximate animated models with local area distortion and deformation degree control. Our method uses an improved quadric error metric guided by a local area distortion measurement as a basic hierarchy. Also  we define a deformation degree parameter to be embedded into the aggregated quadric errors  so areas with large deformation during the animation can be successfully preserved. Finally  a mesh optimization process is proposed to further reduce the geometric distortion for each frame. Our approach is fast  easy to implement  and as a result good quality dynamic approximations with well-preserved sharp features can be generated at any given frame. 2010 SPIE.   An improved method for generating multiresolution animation models (EI CONFERENCE) 会议论文  OAI收割 2009 11th IEEE International Conference on Computer-Aided Design and Computer Graphics, CAD/Graphics 2009, August 19, 2009 - August 21, 2009, Huangshan, China 作者:  Zhang S. 收藏  |  浏览/下载：36/0  |  提交时间：2013/03/25 In computer graphics  animated models are widely used to represent time-varying data. In this paper  we propose an improved method to generate multiresolution animation models. We use a curvature sensitive quadric error metric (QEM) criterion as our basic measurement  which can preserve local features on the surface. We append a deformation weight to the aggregated edge contraction cost for the whole animation to preserve areas with large deformation. At last  we introduce a mesh optimization method to deal with the animation sequence  which can efficiently improve the temporal coherence and reduce visual artifacts. The results show our approach is efficient  easy to implement  and good quality progressive animation models can be generated at any level of detail. 2009 IEEE.