# Targeted change detection in remote sensing images

arXiv: https://arxiv.org/abs/1803.05482 · HTML: https://mlsanity.com/paper/1803.05482/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Mar 2018.

## Built on by (most cited first, 3 of 3)

- [Active learning for interactive satellite image change detection](https://mlsanity.com/paper/2110.04250/) (2021)
- [Reinforcement-based frugal learning for satellite image change detection](https://mlsanity.com/paper/2203.11564/) (2022)
- [Frugal Learning of Virtual Exemplars for Label-Efficient Satellite Image Change Detection](https://mlsanity.com/paper/2203.11559/) (2022)

## Abstract (arXiv)

Recent developments in the remote sensing systems and image processing made it possible to propose a new method of the object classification and detection of the specific changes in the series of satellite Earth images (so called targeted change detection). In this paper we propose a formal problem statement that allows to use effectively the deep learning approach to analyze time-dependent series of remote sensing images. We also introduce a new framework for the development of deep learning models for targeted change detection and demonstrate some cases of business applications it can be used for.