Classification of imbalanced land-use/land-cover data using variational semi-supervised learning

被引：0
|
作者：
Cenggoro, Tjeng Wawan [1 ,2 ]
Isa, Sani M. [3 ]
Kusuma, Gede Putra [3 ]
Pardamean, Bens [2 ,3 ]
机构：
[1] Computer Science Department, School of Computer Science, Bina Nusantara University, Jakarta,11480, Indonesia
[2] Bioinformatics and Data Science Research Center, Bina Nusantara University, Jakarta,11480, Indonesia
[3] Computer Science Department, BINUS Graduate Program, Bina Nusantara University, Jakarta,11480, Indonesia
来源：
Proceedings - 2017 International Conference on Innovative and Creative Information Technology: Computational Intelligence and IoT, ICITech 2017 | 2017年 / 2018-January卷
关键词：
Number:; -; Acronym:; Sponsor:; Nvidia;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Remote sensing
引用
收藏
页码：1 / 6
相关论文
共 50 条
  • [21] INVESTIGATIONS ON THE POTENTIAL OF HYPERSPECTRAL AND SENTINEL-2 DATA FOR LAND-COVER / LAND-USE CLASSIFICATION
    Weinmann, M.
    Maier, P. M.
    Florath, J.
    Weidner, U.
    ISPRS TC I MID-TERM SYMPOSIUM INNOVATIVE SENSING - FROM SENSORS TO METHODS AND APPLICATIONS, 2018, 4-1 : 155 - 162
  • [22] An Object-Oriented Semi-Supervised Land-Use/Land-Cover Change Detection Method Based on Siamese Autoencoder Graph Attention Network
    Wu, Yifan
    Xie, Zhiwei
    Ma, Zaiyang
    Chen, Min
    Zhang, Fengyuan
    Shi, Zhenguo
    Li, Wengang
    Zhai, Shuaizhi
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2024, 17 : 6478 - 6500
  • [23] Radar and optical data integration for land-use/land-cover mapping
    Haack, BN
    Herold, ND
    Bechdol, MA
    PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2000, 66 (06): : 709 - 716
  • [24] General Semi-supervised Possibilistic Fuzzy c-Means clustering for Land-cover Classification
    Dinh Sinh Mai
    Long Thanh Ngo
    PROCEEDINGS OF 2019 11TH INTERNATIONAL CONFERENCE ON KNOWLEDGE AND SYSTEMS ENGINEERING (KSE 2019), 2019, : 133 - 138
  • [25] Radar and optical data integration for land-use/land-cover mapping
    2000, ASPRS, Bethesda, MD, USA (66):
  • [26] SEMI-SUPERVISED LAND COVER CLASSIFICATION USING PI-SAR2 OBSERVATION DATA
    Arima, Yuya
    Kojima, Shoichiro
    Uemoto, Jyunpei
    Konno, Tomohiko
    IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2020, : 2755 - 2758
  • [27] Sources and range of data on land-use and land-cover change in Zimbabwe
    Zinyama, LM
    LAND USE POLICY, 1999, 16 (03) : 161 - 165
  • [28] Automatic Extraction of Training Data Based on Semi-supervised Learning for Time-series Land-cover Mapping
    Kwak, Geun-Ho
    Park, No-Wook
    KOREAN JOURNAL OF REMOTE SENSING, 2022, 38 (05) : 461 - 469
  • [29] From land-use/land-cover to land system science
    Turner, B. L., II
    Lambin, Eric F.
    Verburg, Peter H.
    AMBIO, 2021, 50 (07) : 1291 - 1294
  • [30] Landscape approach for land-use/land-cover classification and mapping at different scales
    Milanova, E
    Alexeev, B
    Sennikova, M
    Kalutskova, N
    Solntsev, V
    Understanding Land-Use and Land-Cover Change in Global and Regional Context, 2005, : 233 - 247
12345