Hello!
I am an Earth Observation Data Scientist specializing in the application of machine learning, deep learning, and big data analytics to satellite and geospatial datasets. With extensive experience in analyzing multi-temporal, multi-sensor Earth observation data, I provide advanced insights for environmental monitoring, land-use change detection, and precision agriculture. My expertise spans the full data science pipeline, from data preprocessing and feature engineering to model development and deployment in geospatial systems.
You can find more information about my skills and experience on my Linkedin profile below.
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I am open to discussing potential collaborations.
My warm regards,
Dr. Fırat Erdem
I'm a postdoctoral researcher in a MarTERA - ERA-NET Cofund.
лип., 2023 - жовт., 2023
•
3 months
Doctoral Fellow
бер., 2019 - бер., 2023
•
4 years
Eskisehir Technical University
бер., 2019 - бер., 2023
•
4 years
Teaching and research assistant in Remote Sensing and GIS department.
бер., 2019 - бер., 2023
•
4 years
Освіта
Ph.D., Remote Sensing and GIS, Eskisehir Technical University
2019 - 2023
•
4 years
Turkey
2019 - 2023
•
4 years
M.S., Remote Sensing and GIS, Yildiz Technical University
2016 - 2018
•
2 years
Turkey
2016 - 2018
•
2 years
B.S, Geomatic Engineering, Karadeniz Technical University
2011 - 2016
•
5 years
Turkey
2011 - 2016
•
5 years
Публікації
Evaluating the effects of texture features on Pinus sylvestris classification
Ecological Informatics
This work aims to investigate the influence of texture features on the categorization of Scots pine using high-resolution aerial images, building upon the proven efficiency of texture features and machine learning in addressing tree species classification challenges.
A nonparametric fuzzy shoreline extraction approach from Sentinel-1A by integration of RASAT imagery
Geo-Marine Letters
The main objective of this study is to extract shorelines from Sentinel-1A radio detection and ranging satellite data using a non-parametric fuzzy approach, by exploiting Turkish multispectral RASAT satellite images.
Tree extraction from multi-scale UAV images using Mask R-CNN with FPN
Remote Sensing Letters
The main aim of this paper is to explore the employed method in images with different scales and tree contents.
Верифікації
Вчасно
100%
В межах бюджету
100%
Рейтинг прийняття
83%
Рейтинг повторного найняття
50%
Запрошення успішно надіслане!
Дякуємо! Ми надіслали на вашу електронну пошту посилання для отримання безкоштовного кредиту.
Під час надсилання електронного листа сталася помилка. Будь ласка, спробуйте ще раз.