中国科学院机构知识库网格系统: 检索

An improved approach to estimating crop lodging percentage with Sentinel-2 imagery using machine learning 期刊论文 OAI收割
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2022, 卷号: 113, 页码: 17
作者: Guan, Haixiang; Huang, Jianxi; Li, Xuecao; Zeng, Yelu; Su, Wei

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收藏 | 浏览/下载：34/0 | 提交时间：2022/09/26

Crop lodging Spatial aggregation Lodging percentage map Spectral bands Vegetation indexes Region scale

Cross-Level Parallel Network for Crowd Counting 期刊论文 OAI收割
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2020, 卷号: 16, 期号: 1, 页码: 566-576
作者: Li, Jing; Xue, Yaokai; Wang, Weiqun; Ouyang, Gaoxiang

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收藏 | 浏览/下载：73/0 | 提交时间：2020/03/30

Convolutional neural network (CNN) cross-level and multiscale features crowd counting density map scale aggregation network

On the criteria to create a susceptibility map to debris flow at a regional scale using Flow-R 期刊论文 OAI收割
Journal of Mountain Science, 2017, 卷号: 14, 期号: 4, 页码: 621-635
作者: PASTORELLO Roberta; MICHELINI Tamara; D'AGOSTINO Vincenzo

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收藏 | 浏览/下载：28/0 | 提交时间：2017/04/07

Debris Flow Susceptibility Map Flow-r Triggering Areas Regional Scale Alpine Valley

Visualizing and Analyzing Video Content With Interactive Scalable Maps 期刊论文 OAI收割
IEEE TRANSACTIONS ON MULTIMEDIA, 2016, 卷号: 18, 期号: 11, 页码: 2171-2183
作者: Ma, Cui-Xia; Liu, Yong-Jin; Zhao, Guozhen; Wang, Hong-An

收藏 | 浏览/下载：26/0 | 提交时间：2016/12/26

Interaction map metaphor multi-scale representation video visualization and analysis

Visualizing and Analyzing Video Content With Interactive Scalable Maps 期刊论文 OAI收割
IEEE TRANSACTIONS ON MULTIMEDIA, 2016, 卷号: 18, 期号: 11, 页码: 2171-2183
Ma, CX; Liu, YJ; Zhao, GZ; Wang, HA

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收藏 | 浏览/下载：23/0 | 提交时间：2016/12/09

Interaction map metaphor multi-scale representation video visualization and analysis

Quantile rank maps: A new tool for understanding individual brain development 期刊论文 OAI收割
NEUROIMAGE, 2015, 卷号: 111, 期号: 1, 页码: 454-463
作者: Chen, Huaihou; Kelly, Clare; Castellanos, F. Xavier; He, Ye; Zuo, Xi-Nian

收藏 | 浏览/下载：60/0 | 提交时间：2015/01/23

Box-Cox transformation Generalized additive models for location scale and shape Quantile rank map MRI Resting-state fMRI Penalized B-splines

A Human Interactome in Three Quantitative Dimensions Organized by Stoichiometries and Abundances 期刊论文 OAI收割
CELL, 2015, 卷号: 163, 期号: 3, 页码: 712-723
Hein, Marco Y.; Hubner, Nina C.; Poser, Ina; Cox, Juergen; Nagaraj, Nagarjuna; Toyoda, Yusuke; Gak, Igor A.; Weisswange, Ina; Mansfeld, Joerg; Buchholz, Frank; Hyman, Anthony A.; Mann, Matthias

收藏 | 浏览/下载：43/0 | 提交时间：2016/05/12

PROTEIN INTERACTION NETWORK MASS-SPECTROMETRY SACCHAROMYCES-CEREVISIAE BAC TRANSGENEOMICS COPY-NUMBER SCALE MAP COMPLEXES REVEALS YEAST ACCURATE

Disaggregating and harmonising soil map units through resampled classification trees SCI/SSCI论文 OAI收割
2014
Odgers N. P.; Sun W.; Mcbratney A. B.; Minasny B.; Clifford D.

收藏 | 浏览/下载：30/0 | 提交时间：2014/12/24

Spatial disaggregation Soil map units Classification trees Legacy soil maps Soil class mapping Digital soil mapping knowledge discovery landscape delineations prediction boundaries models scale area

An improved multi-scale autoconvolution transform 会议论文 OAI收割
Beijing, China, May 13-15, 2014
作者: Shao CY(邵春艳); Ding QH(丁庆海); Luo HB(罗海波)

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收藏 | 浏览/下载：13/0 | 提交时间：2014/12/29

Affine Invariant Feature Multi-scale Autoconvolution N-domain Vectors Included Angle Map N-domain Vectors Angle Map

A line mapping based automatic registration algorithm of infrared and visible images 会议论文 OAI收割
5th International Symposium on Photoelectronic Detection and Imaging (ISPDI) - Infrared Imaging and Applications, Beijing, June 25-27, 2013
作者: Ai R(艾锐); Shi ZL(史泽林); Xu DJ(徐德江); Zhang CS(张程硕)

收藏 | 浏览/下载：36/0 | 提交时间：2013/12/26

There exist complex gray mapping relationships among infrared and visible images because of the different imaging mechanisms. The difficulty of infrared and visible image registration is to find a reasonable similarity definition. In this paper, we develop a novel image similarity called implicit linesegment similarity(ILS) and a registration algorithm of infrared and visible images based on ILS. Essentially, the algorithm achieves image registration by aligning the corresponding line segment features in two images. First, we extract line segment features and record their coordinate positions in one of the images, and map these line segments into the second image based on the geometric transformation model. Then we iteratively maximize the degree of similarity between the line segment features and correspondence regions in the second image to obtain the model parameters. The advantage of doing this is no need directly measuring the gray similarity between the two images. We adopt a multi-resolution analysis method to calculate the model parameters from coarse to fine on Gaussian scale space. The geometric transformation parameters are finally obtained by the improved Powell algorithm. Comparative experiments demonstrate that the proposed algorithm can effectively achieve the automatic registration for infrared and visible images, and under considerable accuracy it makes a more significant improvement on computational efficiency and anti-noise ability than previously proposed algorithms.