143 citations · 143 across the 2 of their papers we have counts for
7 papers
A deep network approach to multitemporal cloud detection
Devis Tuia, Benjamin Kellenberger, Adrian Pérez-Suay +1
We present a deep learning model with temporal memory to detect clouds in image time series acquired by the Seviri imager mounted on the Meteosat Second Generation (MSG) satellite.…
Half a Percent of Labels is Enough: Efficient Animal Detection in UAV Imagery using Deep CNNs and Active Learning
Benjamin Kellenberger, Diego Marcos, Sylvain Lobry +1
We present an Active Learning (AL) strategy for re-using a deep Convolutional Neural Network (CNN)-based object detector on a new dataset. This is of particular interest for wildli…
Scale equivariance in CNNs with vector fields
Diego Marcos, Benjamin Kellenberger, Sylvain Lobry +1
We study the effect of injecting local scale equivariance into Convolutional Neural Networks. This is done by applying each convolutional filter at multiple scales. The output is a…
Detecting Mammals in UAV Images: Best Practices to address a substantially Imbalanced Dataset with Deep Learning
Benjamin Kellenberger, Diego Marcos, Devis Tuia
Knowledge over the number of animals in large wildlife reserves is a vital necessity for park rangers in their efforts to protect endangered species. Manual animal censuses are dan…
Learning deep structured active contours end-to-end
Diego Marcos, Devis Tuia, Benjamin Kellenberger +4
The world is covered with millions of buildings, and precisely knowing each instance's position and extents is vital to a multitude of applications. Recently, automated building fo…
Land cover mapping at very high resolution with rotation equivariant CNNs: towards small yet accurate models
Diego Marcos, Michele Volpi, Benjamin Kellenberger +1
In remote sensing images, the absolute orientation of objects is arbitrary. Depending on an object's orientation and on a sensor's flight path, objects of the same semantic class c…