activity
20182022
most citedDynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation

8 citations · 11 across the 5 of their papers we have counts for

collaborators

10 papers

cs.CV20228 cited

DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation

Aysim Toker, Lukas Kondmann, Mark Weber +10

Earth observation is a fundamental tool for monitoring the evolution of land use in specific areas of interest. Observing and precisely defining change, in this context, requires b…

cs.LG2022

Landscape of Neural Architecture Search across sensors: how much do they differ ?

Kalifou René Traoré, Andrés Camero, Xiao Xiang Zhu

With the rapid rise of neural architecture search, the ability to understand its complexity from the perspective of a search algorithm is desirable. Recently, Traoré et al. have pr…

cs.LG2021

A Data-driven Approach to Neural Architecture Search Initialization

Kalifou René Traoré, Andrés Camero, Xiao Xiang Zhu

Algorithmic design in neural architecture search (NAS) has received a lot of attention, aiming to improve performance and reduce computational cost. Despite the great advances made…

cs.LG20211 cited

Lessons from the Clustering Analysis of a Search Space: A Centroid-based Approach to Initializing NAS

Kalifou Rene Traore, Andrés Camero, Xiao Xiang Zhu

Lots of effort in neural architecture search (NAS) research has been dedicated to algorithmic development, aiming at designing more efficient and less costly methods. Nonetheless,…

cs.NE20212 cited

Reliable and Fast Recurrent Neural Network Architecture Optimization

Andrés Camero, Jamal Toutouh, Enrique Alba

This article introduces Random Error Sampling-based Neuroevolution (RESN), a novel automatic method to optimize recurrent neural network architectures. RESN combines an evolutionar…

cs.LG2020

Bayesian Neural Architecture Search using A Training-Free Performance Metric

Andrés Camero, Hao Wang, Enrique Alba +1

Recurrent neural networks (RNNs) are a powerful approach for time series prediction. However, their performance is strongly affected by their architecture and hyperparameter settin…