216 citations · 228 across the 10 of their papers we have counts for
6 papers · 1 filter
A New Similarity Space Tailored for Supervised Deep Metric Learning
Pedro H. Barros, Fabiane Queiroz, Flavio Figueredo +2
We propose a novel deep metric learning method. Differently from many works on this area, we defined a novel latent space obtained through an autoencoder. The new space, namely S-s…
A Soft Computing Approach for Selecting and Combining Spectral Bands
Juan F. H. Albarracín, Rafael S. Oliveira, Marina Hirota +2
We introduce a soft computing approach for automatically selecting and combining indices from remote sensing multispectral images that can be used for classification tasks. The pro…
Fully Convolutional Open Set Segmentation
Hugo Oliveira, Caio Silva, Gabriel L. S. Machado +2
In semantic segmentation knowing about all existing classes is essential to yield effective results with the majority of existing approaches. However, these methods trained in a Cl…
An End-to-end Framework For Low-Resolution Remote Sensing Semantic Segmentation
Matheus Barros Pereira, Jefersson Alex dos Santos
High-resolution images for remote sensing applications are often not affordable or accessible, especially when in need of a wide temporal span of recordings. Given the easy access…
BrazilDAM: A Benchmark dataset for Tailings Dam Detection
Edemir Ferreira, Matheus Brito, Remis Balaniuk +2
In this work we present BrazilDAM, a novel public dataset based on Sentinel-2 and Landsat-8 satellite images covering all tailings dams cataloged by the Brazilian National Mining A…
Towards Open-Set Semantic Segmentation of Aerial Images
Caio C. V. da Silva, Keiller Nogueira, Hugo N. Oliveira +1
Classical and more recently deep computer vision methods are optimized for visible spectrum images, commonly encoded in grayscale or RGB colorspaces acquired from smartphones or ca…