Skip to content
View Benyaminhosseiny's full-sized avatar

Block or report Benyaminhosseiny

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this userโ€™s behavior. Learn more about reporting abuse.

Report abuse
Benyaminhosseiny/README.md

๐Ÿ™‹โ€โ™‚๏ธ Hi, I'm @Benyaminhosseiny, PhD in remote sensing engineering.

๐Ÿ‘จโ€๐Ÿ’ป My current projects and research works revolve around SAR signal processing, and developing machine/deep learning frameworks for various applications of earth observation.
๐Ÿ“ I try to share my implementations here, but if you came across to my publications and couldn't find the codes, feel free to reach out.

Pinned Loading

  1. Spectral-GBSAR Spectral-GBSAR Public

    Multi-dimensional GBSAR Imaging Using Spectral Estimation: A Model for Fast Displacement Monitoring

    2

  2. 3D-GBInSAR 3D-GBInSAR Public

    Structural displacement monitoring using ground-based synthetic aperture radar: Implementation of 3D displacement vector

    MATLAB 7 1

  3. ClutterFree-GBInSAR ClutterFree-GBInSAR Public

    Structural displacement monitoring using ground-based synthetic aperture radar: Implementation of continuous displacement monitoring and clutter reduction

    MATLAB 1 1

  4. vit-pytorch vit-pytorch Public

    Forked from lucidrains/vit-pytorch

    Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

    Python

  5. WetNet WetNet Public

    WetNet: An Ensemble SAR/Optical Deep model for Wetland Mapping

    Jupyter Notebook 1

  6. NSDL4EO NSDL4EO Public

    A database of over 500 published papers on Earth Observation with Remote Sensing data using Non-Supervised Deep Learning techniques, classified by their learning methods (Un-, Semi-, Self-, Transfeโ€ฆ

    4 1