# Deep Learning Solutions for TanDEM-X-based Forest Classification

Source: [Deep Learning Solutions for TanDEM-X-based Forest Classification](<https://www.sota2.com/research/paper/68fa65551e209131cea09c01>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T21:24:52.728Z

Authors: Antonio Mazza, Francescopaolo Sica

Published: 2019-02-01T11:12:30.000Z

## Abstract

In the last few years, deep learning (DL) has been successfully and massively employed in computer vision for discriminative tasks, such as image classification or object detection. This kind of problems are core to many remote sensing (RS) applications as well, though with domain-specific peculiarities. Therefore, there is a growing interest on the use of DL methods for RS tasks. Here, we consider the forest/non-forest classification problem with TanDEM-X data, and test two state-of-the-art DL models, suitably adapting them to the specific task. Our experiments confirm the great potential of DL methods for RS applications.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1902.00274>)

[PDF](<https://arxiv.org/pdf/1902.00274.pdf>)