中国科学院机构知识库网格系统: 检索

Offshore Hydrocarbon Exploitation Target Extraction Based on Time-Series Night Light Remote Sensing Images and Machine Learning Models: A Comparison of Six Machine Learning Algorithms and Their Multi-Feature Importance 期刊论文 OAI收割
REMOTE SENSING, 2023, 卷号: 15, 期号: 7, 页码: 1843
作者: Ma, Rui; Wu, Wenzhou; Wang, Qi; Liu, Na; Chang, Yutong

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收藏 | 浏览/下载：18/0 | 提交时间：2023/05/06

offshore hydrocarbon exploitation targets night light remote sensing images feature increment strategy machine learning model feature evaluation

Recent Advances in Pedestrian Navigation Activity Recognition: A Review 期刊论文 OAI收割
IEEE SENSORS JOURNAL, 2022, 卷号: 22, 期号: 8, 页码: 7499-7518
作者: Wang, Qu; Luo, Haiyong; Wang, Jianquan; Sun, Lei; Ma, Zhangchao

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收藏 | 浏览/下载：39/0 | 提交时间：2022/12/07

Activity recognition Sensors Navigation Legged locomotion Performance evaluation Hidden Markov models Feature extraction Pedestrian positioning human activity recognition pedestrian navigation activity public dataset

Exploring the Representativity of Art Paintings 期刊论文 OAI收割
IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 卷号: 23, 页码: 2794-2805
作者: Deng, Yingying; Tang, Fan; Dong, Weiming; Ma, Chongyang; Huang, Feiyue

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收藏 | 浏览/下载：45/0 | 提交时间：2021/11/03

Painting Art Image color analysis Feature extraction Task analysis Engineering profession Electronic mail Representativity style enhancement feature representation artwork evaluation

Performance evaluation of global hydrological models in six large Pan-Arctic watersheds 期刊论文 OAI收割
CLIMATIC CHANGE, 2020, 页码: 23
作者: Gaedeke, Anne; Krysanova, Valentina; Aryal, Aashutosh; Chang, Jinfeng; Grillakis, Manolis

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收藏 | 浏览/下载：30/0 | 提交时间：2021/03/16

Global Water Models Model performance Model evaluation Arctic watersheds Boruta feature selection

Synthesized computational aesthetic evaluation of photos 期刊论文 OAI收割
neurocomputing, 2016, 卷号: 172, 页码: 244-252
作者: Wang, Weining; Cai, Dong; Wang, Li; Huang, Qinghua; Xu, Xiangmin

收藏 | 浏览/下载：34/0 | 提交时间：2015/12/25

Aesthetic evaluation Feature extraction Classification Mobile application Photo

Semi-supervised learning and feature evaluation for RGB-D object recognition 期刊论文 OAI收割
COMPUTER VISION AND IMAGE UNDERSTANDING, 2015, 卷号: 139, 页码: 149-160
作者: Cheng, Yanhua; Zhao, Xin; Huang, Kaiqi; Tan, Tieniu

收藏 | 浏览/下载：27/0 | 提交时间：2015/10/26

RGB-D Object recognition Feature representation Feature evaluation Semi-supervised learning

复杂场景下基于视觉注意显著性特征目标跟踪方法研究 学位论文 OAI收割
工学博士, 中国科学院自动化研究所: 中国科学院大学, 2015
作者: 刘林山

收藏 | 浏览/下载：104/0 | 提交时间：2015/09/02

视觉注意显著性特征区分度判别力自适应性评价机制目标跟踪 Visual attention saliency feature distinctions degree discriminant adaptability evaluation mechanism object tracking

基于评论挖掘的软件评价系统 期刊论文 OAI收割
计算机应用与软件, 2014, 卷号: 31, 期号: 7, 页码: 1-4,85
卢忠浩; 杨达; 李娟

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收藏 | 浏览/下载：42/0 | 提交时间：2014/12/16

软件评论挖掘软件评价软件特征提取极性分析软件特征聚类 Web系统 Software reviews mining Software evaluation Software feature extraction Polarity analysis Software feature clustering Web system

A Novel Algorithm for View and Illumination Invariant Image Matching 期刊论文 OAI收割
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2012, 卷号: 21, 期号: 1, 页码: 229-240
作者: Yu, Yinan; Huang, Kaiqi; Chen, Wei; Tan, Tieniu

收藏 | 浏览/下载：25/0 | 提交时间：2015/08/12

Feature detector evaluation image matching valid angle (VA) valid illumination (VI)

Evaluation of the operating range for ground-based infrared imaging tracking system (EI CONFERENCE) 会议论文 OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China
作者: Zhang Z.-D.

收藏 | 浏览/下载：50/0 | 提交时间：2013/03/25

Ground-based infrared imaging tracking system (GIITS) is of great importance for aerial target warning and guard. The operating range is one of the key performance specifications on the other which should be calculated calculate the radiation power received on the detector in order to analysis whether the output signal meets the detection requirements or not analyzed and studied during the whole GIITS design process. The operating range is mostly influenced by a few factors without considering the effect of the background radiation. By improving of the traditional method including atmospheric attenuation a new operating range calculation model of the GIITS was established based on two requirements. One is that the image size of observed target should meet the requirement of the processor signal extraction. The number of the pixel occupied by target image should be more than 9. The other is that the signal noise ratio (SNR) of the GIITS should not be less than 5 to meet the requirements of the target detection probability and spatial frequency. The SNR calculation equation in form of energy is deduced and the radiation characteristic of the observed target and background are analyzed. When evaluate the operating range of the GIITS using the new method the performance of GIITS and feature of target and background. This paper firstly makes analysis and summarization on the definite localizations of the traditional operating range equation of the GIITS. The localizations are mainly in two aspects. On one hand we should successively calculate two operating range values according to two requirements mentioned above and choose the minimum value as the analytic result. In the end the dispersion of the image and the effect of image dispersion are not considered in the traditional method an evaluation of operating range for fighter aircraft is accomplished as an example. The influence factors in every aspect on operating range were explored by the calculated result. The new operating range calculation model provides the theoretical basis for the design and applications as well as the comprehensive evaluation of a GIITS. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).