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COMPARATIVE STUDY ON DEEP NEURAL NETWORK MODELS FOR CROP CLASSIFICATION USING TIME SERIES POLSAR AND OPTICAL DATA
Deep neural networks CNNs LSTMs ConvLSTMs Crop classification
2019/2/28
Crop classification is an important task in many crop monitoring applications. Satellite remote sensing has provided easy, reliable, and fast approaches to crop classification task. In this study, a c...
THE RESEARCH ON DRYLAND CROP CLASSIFICATION BASED ON THE FUSION OF SENTINEL-1A SAR AND OPTICAL IMAGES
Crop Classification Fusion Sentinel-1A Synthetic Aperture Radar Object-Oriented Technique
2018/5/15
In recent years, the quick upgrading and improvement of SAR sensors provide beneficial complements for the traditional optical remote sensing in the aspects of theory, technology and data. In this pap...
Automatic Training Sample Selection for a Multi-Evidence Based Crop Classification Approach
Crop Classification Training Vector Neural Satellite Imagery Learning
2014/9/29
An approach to use the available agricultural parcel information to automatically select training samples for crop classification is investigated. Previous research addressed the multi-evidence crop c...
AUTOMATIC TRAINING SITE SELECTION FOR AGRICULTURAL CROP CLASSIFICATION: A CASE STUDY ON KARACABEY PLAIN, TURKEY
Crop Classification Agriculture Segmentation Mean-Shift Kompsat-2
2014/6/5
This study implements a traditional supervised classification method to an optical image composed of agricultural crops by means of
a unique way, selecting the training samples automatically. Panch...