机构

• 自动化研究所 [4]
• 金属研究所 [3]
• 地理科学与资源研究所 [3]
• 长春光学精密机械与物... [3]
• 合肥物质科学研究院 [3]
• 计算技术研究所 [1]
• 更多

采集方式

• OAI收割 [19]
• iSwitch采集 [2]

内容类型

• 期刊论文 [17]
• 会议论文 [3]
• 学位论文 [1]

发表日期

• 2022 [1]
• 2021 [2]
• 2020 [4]
• 2019 [4]
• 2018 [1]
• 2017 [2]
• 更多

学科主题

• Materials ... [1]
• Materials ... [1]
• Metallurgy... [1]

筛选

浏览/检索结果: 共21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发表日期升序发表日期降序提交时间升序提交时间降序作者升序作者降序 Pest Region Detection in Complex Backgrounds via Contextual Information and Multi-Scale Mixed Attention Mechanism 期刊论文  OAI收割 AGRICULTURE-BASEL, 2022, 卷号: 12 作者:  Zhang, Wei;  Sun, Youqiang;  Huang, He;  Pei, Haotian;  Sheng, Jiajia   |  收藏  |  浏览/下载：52/0  |  提交时间：2022/12/23 early pest control  pest region  small object  context  attention mechanism  feature fusion   A study on nuclear analysis of the divertor region of the CFETR 期刊论文  OAI收割 PLASMA SCIENCE & TECHNOLOGY, 2021, 卷号: 23 作者:  Saidahmed, Rayyan;  Yao, Damao;  Wu, Qiuran;  Liu, Songlin;  Xu, Tiejun   |  收藏  |  浏览/下载：69/0  |  提交时间：2021/11/15 CFETR  fusion reactor  divertor  nuclear analysis  divertor region   Offline signature verification using a region based deep metric learning network 期刊论文  OAI收割 PATTERN RECOGNITION, 2021, 卷号: 118, 页码: 12 作者:  Liu, Li;  Huang, Linlin;  Yin, Fei;  Chen, Youbin   |  收藏  |  浏览/下载：35/0  |  提交时间：2021/08/15 Signature verification  Convolutional siamese network  Deep metric learning  Region fusion   Cropland data fusion and correction using spatial analysis techniques and the Google Earth Engine 期刊论文  OAI收割 GISCIENCE & REMOTE SENSING, 2020, 页码: 20 作者:  Li, Kewei;  Xu, Erqi   |  收藏  |  浏览/下载：25/0  |  提交时间：2021/03/16 Cropland  data fusion  Google Earth Engine  belt and road region   Cropland data fusion and correction using spatial analysis techniques and the Google Earth Engine 期刊论文  OAI收割 GISCIENCE & REMOTE SENSING, 2020, 页码: 20 作者:  Li, Kewei;  Xu, Erqi   |  收藏  |  浏览/下载：18/0  |  提交时间：2021/03/16 Cropland  data fusion  Google Earth Engine  belt and road region   Thermal Infrared Tracking using Multi-stages Deep Features Fusion 会议论文  OAI收割 Hefei, China, 2020-08-22 作者:  Zhang, Ximing;  Chen, Rongli;  Liu, Gang;  Li, Xuyang;  Luo, Shujuan   |  收藏  |  浏览/下载：43/0  |  提交时间：2020/10/30 Thermal Infrared Tracking  Multi-stages Networks  Deep Features Fusion  Siamese Networks  Region Proposal Networks   AF-RCNN: An anchor-free convolutional neural network for multi-categories agricultural pest detection 期刊论文  OAI收割 COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2020, 卷号: 174 作者:  Jiao, Lin;  Dong, Shifeng;  Zhang, Shengyu;  Xie, Chengjun;  Wang, Hongqiang   |  收藏  |  浏览/下载：54/0  |  提交时间：2020/11/26 Agricultural pest detection  Fusion features  Anchor-free  RCNN  Region proposals   Combining kernel-driven and fusion-based methods to generate daily high-spatial-resolution land surface temperatures 期刊论文  OAI收割 REMOTE SENSING OF ENVIRONMENT, 2019, 卷号: 224, 页码: 259-274 作者:  Xia, Haiping;  Chen, Yunhao;  Li, Ying;  Quan, Jinling   |  收藏  |  浏览/下载：68/0  |  提交时间：2019/05/22 Temperature disaggregation  Thermal sharpening  Spatiotemporal fusion  Heterogeneous region  TPS interpolation   Dynamic Identification of Critical Nodes and Regions in Power Grid Based on Spatio-Temporal Attribute Fusion of Voltage Trajectory 期刊论文  OAI收割 ENERGIES, 2019, 卷号: 12, 期号: 5, 页码: 16 作者:  Bai, Xiwei;  Liu, Daowei;  Tan, Jie;  Yang, Hongying;  Zheng, Hengfeng   |  收藏  |  浏览/下载：43/0  |  提交时间：2019/04/23 critical node  critical region  spatio-temporal attribute fusion  node voltage trajectory   The Cat's Eye Effect Target Recognition Method Based on Visual Attention 期刊论文  OAI收割 Chinese Journal of Electronics, 2019, 卷号: 28, 期号: 5, 页码: 1080-1086 作者:  X.B.Wang;  J.Zhang;  S.H.Wang   |  收藏  |  浏览/下载：35/0  |  提交时间：2020/08/24 feature extraction,image fusion,object detection,target-saliency map,target region,Cat's eye effect target recognition method,visual,attention,second-directional derivative filter,directional channels,morphological method,potential targets exist,designed saliency fusing,method,candidate targets,Cat's eye effect target recognition method,based on visual attention (CTRVA),Target recognition,Saliency map,Engineering