3.2k citations · 3.7k across the 6 of their papers we have counts for
6 papers
Adaptive Compression-based Lifelong Learning
Shivangi Srivastava, Maxim Berman, Matthew B. Blaschko +1
The problem of a deep learning model losing performance on a previously learned task when fine-tuned to a new one is a phenomenon known as Catastrophic forgetting. There are two ma…
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…
Understanding urban landuse from the above and ground perspectives: a deep learning, multimodal solution
Shivangi Srivastava, John E. Vargas-Muñoz, Devis Tuia
Landuse characterization is important for urban planning. It is traditionally performed with field surveys or manual photo interpretation, two practices that are time-consuming and…
Deep learning in remote sensing: a review
Xiao Xiang Zhu, Devis Tuia, Lichao Mou +4
Standing at the paradigm shift towards data-intensive science, machine learning techniques are becoming increasingly important. In particular, as a major breakthrough in the field,…
Detecting animals in African Savanna with UAVs and the crowds
Nicolas Rey, Michele Volpi, Stéphane Joost +1
Unmanned aerial vehicles (UAVs) offer new opportunities for wildlife monitoring, with several advantages over traditional field-based methods. They have readily been used to count…
Towards seamless multi-view scene analysis from satellite to street-level
Sébastien Lefèvre, Devis Tuia, Jan Dirk Wegner +2
In this paper, we discuss and review how combined multi-view imagery from satellite to street-level can benefit scene analysis. Numerous works exist that merge information from rem…