Machine learning approach to fusion of high and low resolution imagery for improved target classification

被引：0
|
作者：
Ilin, Roman [1 ]
机构：
[1] Air Force Res Lab, Sensors Directorate, Wright Patterson AFB, OH 45433 USA
来源：
IEEE NATIONAL AEROSPACE AND ELECTRONICS CONFERENCE (NAECON 2014) | 2014年
关键词：
LUPI; SVM; Clustering; Object Classification;
D O I：
暂无
中图分类号：
V [航空、航天];
学科分类号：
08 ; 0825 ;
摘要：
this work utilizes high resolution images in order to improve the classification accuracy on low resolution images. The approach is based on the machine learning paradigm called LUPI - "Learning Using Privileged Information". In this contribution, the LUPI paradigm is demonstrated on images from the Caltech 101 dataset.
引用
收藏
页码：195 / 199
页数：5
相关论文
共 50 条
  • [1] A target fusion-based approach for classifying high spatial resolution imagery
    Huang, PS
    Tu, TM
    2003 IEEE WORKSHOP ON ADVANCES IN TECHNIQUES FOR ANALYSIS OF REMOTELY SENSED DATA, 2004, : 175 - 181
  • [2] Target-cluster fusion approach for classifying high resolution IKONOS imagery
    Su, Y
    Huang, PS
    Lin, CF
    Tu, TM
    IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING, 2004, 151 (04): : 241 - 249
  • [3] Improved support vector machine target classification algorithm for low-resolution radar
    Chen Z.
    Gu H.
    Su W.
    Wang Z.
    1600, Chinese Institute of Electronics (39): : 2456 - 2462
  • [4] IMPROVING URBAN TREE SPECIES CLASSIFICATION WITH HIGH RESOLUTION SATELLITE IMAGERY AND MACHINE LEARNING
    Wenger, Romain
    Bressant, Clement
    Roettele, Lucie
    Forestier, Germain
    Puissant, Anne
    IGARSS 2024-2024 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, IGARSS 2024, 2024, : 4679 - 4682
  • [5] A wavelet integrated image fusion approach for target detection in very high resolution satellite imagery
    Zhang, Y
    Hong, G
    SIGNAL PROCESSING, SENSOR FUSION, AND TARGET RECOGNITION XIV, 2005, 5809 : 330 - +
  • [6] A Novel Feature Fusion Approach for Classification of Motor Imagery EEG Based on Hierarchical Extreme Learning Machine
    Duan, Lijuan
    Lian, Zhaoyang
    Qiao, Yuanhua
    Chen, Juncheng
    Miao, Jun
    Li, Mingai
    COGNITIVE COMPUTATION, 2024, 16 (02) : 566 - 580
  • [7] A Novel Feature Fusion Approach for Classification of Motor Imagery EEG Based on Hierarchical Extreme Learning Machine
    Lijuan Duan
    Zhaoyang Lian
    Yuanhua Qiao
    Juncheng Chen
    Jun Miao
    Mingai Li
    Cognitive Computation, 2024, 16 : 566 - 580
  • [8] Classification of high resolution imagery based on fusion of multiscale texture features
    Liu, Jinxiu
    Liu, Huiping
    Lv, Ying
    Xue, Xiaojuan
    35TH INTERNATIONAL SYMPOSIUM ON REMOTE SENSING OF ENVIRONMENT (ISRSE35), 2014, 17
  • [9] Machine learning with high-resolution aerial imagery and data fusion to improve and automate the detection of wetlands
    Lopez-Tapia, Santiago
    Ruiz, Pablo
    Smith, Mitchell
    Matthews, Jeffrey
    Zercher, Bradley
    Sydorenko, Liliana
    Varia, Neelanshi
    Jin, Yuanzhe
    Wang, Minzi
    Dunn, Jennifer B.
    Katsaggelos, Aggelos K.
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2021, 105
  • [10] Machine Learning-Based Classification for Crop-Type Mapping Using the Fusion of High-Resolution Satellite Imagery in a Semiarid Area
    Moumni, Aicha
    Lahrouni, Abderrahman
    SCIENTIFICA, 2021, 2021
12345