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This code is for the paper "PolSAR Image Classification based on Deep Convolutional Neural Networks and Wavelet Transformation" that is published in the IEEE Geoscience and Remote Sensing Letters journal.

License: Apache License 2.0

Jupyter Notebook 100.00%
cnn-classification haar-features ieee polsar remote-sensing cnn convolutional-neural-networks deep-learning image-classification remote-sensing-image

deepcnn_polsar's Introduction

Ali Jamali

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๐Ÿ”ฌ Ali Jamali is an expert in satellite and airborne remote sensing research and development with a Ph.D. degree in Geoinformatics.

Experiences:

  • Developed cutting-edge methods for various remote sensing applications (e.g., deforestation mapping, flood monitoring, wetlands mapping and monitoring)
  • Experience working with top scientists in remote sensing and computer science
  • Extensive industrial and academic R&D experience
  • Proven academic research and development capability in digital image processing for optical and SAR remote sensing

Areas of Interest:

  • Geoinformatics, Geographical Information Science (GIS), Geospatial data analysis
  • Remote Sensing, Earth Observation, Synthetic Aperture Radar (SAR), Multispectral, Hyperspectral
  • Large-scale area monitoring, change detection, time series analysis, site monitoring
  • Classification, Segmentation
  • Image Processing, Computer Vision, Deep Learning, Machine Learning, AI, Geo AI

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