Deep Domain Adaptation for Detecting Bomb Craters in Aerial Images

by   Marco Geiger, et al.

The aftermath of air raids can still be seen for decades after the devastating events. Unexploded ordnance (UXO) is an immense danger to human life and the environment. Through the assessment of wartime images, experts can infer the occurrence of a dud. The current manual analysis process is expensive and time-consuming, thus automated detection of bomb craters by using deep learning is a promising way to improve the UXO disposal process. However, these methods require a large amount of manually labeled training data. This work leverages domain adaptation with moon surface images to address the problem of automated bomb crater detection with deep learning under the constraint of limited training data. This paper contributes to both academia and practice (1) by providing a solution approach for automated bomb crater detection with limited training data and (2) by demonstrating the usability and associated challenges of using synthetic images for domain adaptation.


page 4

page 5

page 6


Adversarial Domain Adaptation for Duplicate Question Detection

We address the problem of detecting duplicate questions in forums, which...

An Out-of-Domain Synapse Detection Challenge for Microwasp Brain Connectomes

The size of image stacks in connectomics studies now reaches the terabyt...

Deep Learning of Crystalline Defects from TEM images: A Solution for the Problem of "Never Enough Training Data"

Crystalline defects, such as line-like dislocations, play an important r...

Discovering Long-period Exoplanets using Deep Learning with Citizen Science Labels

Automated planetary transit detection has become vital to prioritize can...

Using Simulated Data to Generate Images of Climate Change

Generative adversarial networks (GANs) used in domain adaptation tasks h...

Domain Adaptation Using Adversarial Learning for Autonomous Navigation

Autonomous navigation has become an increasingly popular machine learnin...

Colonoscopy Polyp Detection: Domain Adaptation From Medical Report Images to Real-time Videos

Automatic colorectal polyp detection in colonoscopy video is a fundament...

Please sign up or login with your details

Forgot password? Click here to reset