Deep Learning in Remote Sensing
Understanding remote sensing data and doing deep learning studies on this data are among the most important issues of today.
Problems caused by natural disasters, detection of abnormal situations on earth, intervention in city planning and more, it is possible by studying deep learning on remote sensing data.
This tutorial series includes my research, presentations, slides, recommendations and resources for the remote sensing area.
I created a GitHub repo for Deep Learning in Remote Sensing Tutorial. It will be updated and renewed over time. I recommend you star this repo:
I made a 4-week webinar on Deep Learning in Remote Sensing subject. It was for the beginner level on deep learning. The slides and notes were in English, the webinar videos were in Turkish. All slides will be converted to cheat sheets and detailed notes will be added. You can find the presentations and slides below.
Episode 1 — Introduction to Deep Learning
This episode is made for beginners on Deep Learning and has suggestions, tricks and more.
Learning the fundamentals of deep learning and image processing is very important at the beginning. Here you can access the Episode-1 slide.
Here, You can find the webinar for Episode 1 that I gave. The webinar language is Turkish.
The first episode contains these topics;
1-AI, ML, DL, Data terms and differences
2-Computer Vision ıntroduction
3-Computer Vision Usage Areas
4-Types of Deep Learning
5-Creating Model — Example CNN
6-DL Frameworks and Libraries
7-DL Working Environments
8-Suggested Resources
Episode 2 — Tensorflow, Github and Code Review
This episode was made for the second week and beginners. After the first week, I wanted to talk about Tensorflow, other frameworks, examples for beginner and deep learning projects. Here you can access the Episode-2 slide.
Here, You can find the webinar for Episode 2 that I gave. The webinar language is Turkish.
The second episode contains these topics;
1-What is Tensorflow?
2-Why we use Tensorflow?
3-What is Tensorflow differences for other frameworks?
4-Github Usage — Source Code search, find and review
Episode 3 — Raster Imagery Basics
This episode made for especially remote sensing and deep learning. After the first two weeks, I wanted to give about remote sensing with deep learning and make the segmentation example. You can access the third week slides here.
Here, You can find the webinar for Episode 3 that I gave. The webinar language is Turkish.
1-Some Examples in Remote Sensing and Deep Learning
2-Data Basics (Various Data Types (Hyperspectral — SAR etc))
3-ML and DL Based Object Detection
4-Object Detection Algorithms
5-Object Detection Dataset
6-Some Good Sources for Segmentation, Object Detection etc based process
7-Practical Session and Sources
Episode 4 — Deep Learning on 3D Point Clouds
In the last episode, we introduce the topic of 3D Point cloud. You can access the last episode slides here.
Here, You can find the webinar for Episode 4 that I gave. The webinar language is Turkish.
The last episode contains these topics;
1-Capturing a 3D World
2–3D Problems and Deep Learning Techniques
3–3D Cloud Point
4-Deep Learning on 3D Point
5-Public Datasets for 3D
You can share your suggestions and comments about working by contacting me. All my contact addresses are on my website;
