15 citations · 43 across the 14 of their papers we have counts for
8 papers · 1 filter
Group-invariant Coresets for Data-efficient Active Learning
L. C. Ayres, J. C. M. Bermudez, S. J. M. de Almeida +1
Active learning reduces labeling cost by querying the most informative unlabeled samples, but standard coreset methods ignore known data symmetries and can waste budget on transfor…
Robust Recursive Fusion of Multiresolution Multispectral Images with Location-Aware Neural Networks
Haoqing Li, Ricardo Borsoi, Tales Imbiriba +1
Multiresolution image fusion is a key problem for real-time satellite imaging and plays a central role in detecting and monitoring natural phenomena such as floods. It aims to solv…
Hierarchical Homogeneity-Based Superpixel Segmentation: Application to Hyperspectral Image Analysis
Luciano Carvalho Ayres, Sérgio José Melo de Almeida, José Carlos Moreira Bermudez +1
Hyperspectral image (HI) analysis approaches have recently become increasingly complex and sophisticated. Recently, the combination of spectral-spatial information and superpixel t…
Learning Interpretable Deep Disentangled Neural Networks for Hyperspectral Unmixing
Ricardo Augusto Borsoi, Deniz Erdoğmuş, Tales Imbiriba
Although considerable effort has been dedicated to improving the solution to the hyperspectral unmixing problem, non-idealities such as complex radiation scattering and endmember v…
Dynamical Hyperspectral Unmixing with Variational Recurrent Neural Networks
Ricardo Augusto Borsoi, Tales Imbiriba, Pau Closas
Multitemporal hyperspectral unmixing (MTHU) is a fundamental tool in the analysis of hyperspectral image sequences. It reveals the dynamical evolution of the materials (endmembers)…
Online multi-resolution fusion of space-borne multispectral images
Haoqing Li, Bhavia Duvviri, Ricardo Borsoi +4
Satellite imaging has a central role in monitoring, detecting and estimating the intensity of key natural phenomena. One important feature of satellite images is the trade-off betw…