Related references
Note: Only part of the references are listed.Deep Learning for Effective Refugee Tent Extraction Near Syria-Jordan Border
Yan Lu et al.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (2021)
Applying Fully Convolutional Architectures for Semantic Segmentation of a Single Tree Species in Urban Environment on High Resolution UAV Optical Imagery
Daliana Lobo Torres et al.
SENSORS (2020)
How Well Do Deep Learning-Based Methods for Land Cover Classification and Object Detection Perform on High Resolution Remote Sensing Imagery?
Xin Zhang et al.
REMOTE SENSING (2020)
Tree, Shrub, and Grass Classification Using Only RGB Images
Bulent Ayhan et al.
REMOTE SENSING (2020)
Multi-scale Adaptive Feature Fusion Network for Semantic Segmentation in Remote Sensing Images
Ronghua Shang et al.
REMOTE SENSING (2020)
Improving Land Cover Classification Using Extended Multi-Attribute Profiles (EMAP) Enhanced Color, Near Infrared, and LiDAR Data
Chiman Kwan et al.
REMOTE SENSING (2020)
Deep Learning for Land Cover Classification Using Only a Few Bands
Chiman Kwan et al.
REMOTE SENSING (2020)
Object-Based Change Detection Using Multiple Classifiers and Multi-Scale Uncertainty Analysis
Kun Tan et al.
REMOTE SENSING (2019)
Smallholder Crop Area Mapped with a Semantic Segmentation Deep Learning Method
Zhenrong Du et al.
REMOTE SENSING (2019)
Deep Feature Fusion with Integration of Residual Connection and Attention Model for Classification of VHR Remote Sensing Images
Jicheng Wang et al.
REMOTE SENSING (2019)
Semi-Automated Emergency Landing Site Selection Approach for UAVs
Bulent Ayhan et al.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS (2019)
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
Liang-Chieh Chen et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2018)
Algorithms for semantic segmentation of multispectral remote sensing imagery using deep learning
Ronald Kemker et al.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2018)
Urban land-use mapping using a deep convolutional neural network with high spatial resolution multispectral remote sensing imagery
Bo Huang et al.
REMOTE SENSING OF ENVIRONMENT (2018)
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Vijay Badrinarayanan et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2017)
Deep-learning Versus OBIA for Scattered Shrub Detection with Google Earth Imagery: Ziziphus lotus as Case Study
Emilio Guirado et al.
REMOTE SENSING (2017)
Semantic Segmentation of Remote Sensing Imagery Using Object-Based Markov Random Field Model With Regional Penalties
Chen Zheng et al.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2015)
Ndvi: Vegetation change detection using remote sensing and gis - A case study of Vellore District
Meera G. Gandhi et al.
3RD INTERNATIONAL CONFERENCE ON RECENT TRENDS IN COMPUTING 2015 (ICRTC-2015) (2015)
An Object-Based Approach for Mapping Shrub and Tree Cover on Grassland Habitats by Use of LiDAR and CIR Orthoimages
Thomas Hellesen et al.
REMOTE SENSING (2013)
Feature Extraction using Normalized Difference Vegetation Index (NDVI): a Case Study of Jabalpur City
A. K. Bhandari et al.
2ND INTERNATIONAL CONFERENCE ON COMMUNICATION, COMPUTING & SECURITY [ICCCS-2012] (2012)
Detecting the impact of the Grain for Green program on the mean annual vegetation cover in the Shaanxi province, China using SPOT-VGT NDVI data
Hongjian Zhou et al.
LAND USE POLICY (2009)
Vegetation mapping for landmine detection using long-wave hyperspectral imagery
Alina Zare et al.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2008)
Share Paper
