机构

• 地理科学与资源研究所 [1]
• 长春光学精密机械与物... [1]
• 武汉物理与数学研究所 [1]
• 植物研究所 [1]

采集方式

• OAI收割 [4]

内容类型

• 期刊论文 [3]
• 会议论文 [1]

发表日期

• 2019 [2]
• 2013 [1]
• 2012 [1]

学科主题

• Ecology [1]
• Evolutiona... [1]

筛选

浏览/检索结果: 共4条，第1-4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 Is there coordination of leaf and fine root traits at local scales? A test in temperate forest swamps 期刊论文  OAI收割 ECOLOGY AND EVOLUTION, 2019, 卷号: 9, 期号: 15, 页码: 8714-8723 作者:  Hu, Yu-Kun;  Pan, Xu;  Yang, Xue-Jun;  Liu, Guo-Fang;  Liu, Xu-Yan   |  收藏  |  浏览/下载：80/0  |  提交时间：2019/09/24 aboveground-belowground linkages  fine roots  forest swamps  functional traits  local scales  successional gradient   Is there coordination of leaf and fine root traits at local scales? A test in temperate forest swamps 期刊论文  OAI收割 ECOLOGY AND EVOLUTION, 2019, 卷号: 9, 期号: 15, 页码: 8714-8723 作者:  Hu, Yu-Kun;  Pan, Xu;  Yang, Xue-Jun;  Liu, Guo-Fang;  Liu, Xu-Yan   |  收藏  |  浏览/下载：17/0  |  提交时间：2022/01/06 aboveground-belowground linkages  fine roots  forest swamps  functional traits  local scales  successional gradient   Dynamic simulation and 2D multiple scales and multiple sources within basin geothermal field 期刊论文  OAI收割 INTERNATIONAL JOURNAL OF OIL GAS AND COAL TECHNOLOGY, 2013, 卷号: 6, 期号: 1-2, 页码: 103-119 作者:   收藏  |  浏览/下载：13/0  |  提交时间：2016/01/25 basin geothermal field  additional geothermal field  dynamic simulation  multiple scales  local grid increasing   Features extraction and matching of teeth image based on the SIFT algorithm (EI CONFERENCE) 会议论文  OAI收割 2012 2nd International Conference on Computer Application and System Modeling, ICCASM 2012, July 27, 2012 - July 29, 2012, Shenyang, China 作者:  Wang X.;  Wang X.;  Wang X. 收藏  |  浏览/下载：28/0  |  提交时间：2013/03/25 Using of SIFT algorithm in the image of teeth model  can detect the features of the teeth image effectively. In this approach  first  search over all scales and image locations by using a difference-of-Gaussian function to identify potential interest points that are invariant to scale and orientation. Second  select keypoints based on measures of their stability and a detailed model is fit to determine location and scale at each candidate location. Third  assign one or more orientations to each keypoint location based on local image gradient directions. Last  measure the local image gradients at the selected scale in the region around each keypoint. And then use the KNN algorithm to match the features. Through lots of experiments and comparing with other feature extraction methods  this method can detect the features of the teeth model effectively  and offer some available parameters for 3D reconstruction of the teeth model. the authors.