no code implementations • 29 Mar 2023 • Dajana Dimitrić, Mitar Simić, Vladimir Risojević
In this paper we deal with the problem of detecting remote sensing images coming from a different distribution compared to the training data - out of distribution images.
1 code implementation • 5 Nov 2021 • Vladimir Risojević, Vladan Stojnić
Recently, the availability of larger high resolution remote sensing (HRRS) image datasets and progress in self-supervised learning have brought up the questions of whether supervised ImageNet pre-training is still necessary for remote sensing scene classification and would supervised pre-training on HRRS image datasets or self-supervised pre-training on ImageNet achieve better results on target remote sensing scene classification tasks.
Ranked #1 on Multi-Label Classification on MLRSNet
1 code implementation • 14 Apr 2021 • Vladan Stojnić, Vladimir Risojević
We show that, for the downstream task of remote sensing image classification, using self-supervised pre-training on remote sensing images can give better results than using supervised pre-training on images of natural scenes.
1 code implementation • 11 Feb 2021 • Vladan Stojnić, Vladimir Risojević, Mario Muštra, Vedran Jovanović, Janja Filipi, Nikola Kezić, and Zdenka Babić
To circumvent this problem, we propose training a CNN using synthetic videos generated by adding small blob-like objects to video sequences with real-world backgrounds.
Ranked #1 on Small Object Detection on Bee4Exp Honeybee Detection (using extra training data)