research
∙
07/20/2023
Deep learning for classification of noisy QR codes
We wish to define the limits of a classical classification model based o...
share
research
∙
09/24/2021
How to find a good image-text embedding for remote sensing visual question answering?
Visual question answering (VQA) has recently been introduced to remote s...
research
∙
09/18/2020
Contextual Semantic Interpretability
Convolutional neural networks (CNN) are known to learn an image represen...
research
∙
03/16/2020
RSVQA: Visual Question Answering for Remote Sensing Data
This paper introduces the task of visual question answering for remote s...
research
∙
09/18/2019
Semantically Interpretable Activation Maps: what-where-how explanations within CNNs
A main issue preventing the use of Convolutional Neural Networks (CNN) i...
research
∙
07/17/2019
Half a Percent of Labels is Enough: Efficient Animal Detection in UAV Imagery using Deep CNNs and Active Learning
We present an Active Learning (AL) strategy for re-using a deep Convolut...
research
∙
04/08/2019
Pushing the right boundaries matters! Wasserstein Adversarial Training for Label Noise
Noisy labels often occur in vision datasets, especially when they are is...
research
∙
01/24/2019
Correcting rural building annotations in OpenStreetMap using convolutional neural networks
Rural building mapping is paramount to support demographic studies and p...
research
∙
07/31/2018
