421 citations · 1.4k across the 28 of their papers we have counts for
29 papers
Risk-based regulation for all: The need and a method for a wide adoption solution for data-driven inspection targeting
Celso H. H. Ribas, José C. M. Bermudez
Access to data and data processing, including the use of machine learning techniques, has become significantly easier and cheaper in recent years. Nevertheless, solutions that can…
A Pathology-Based Machine Learning Method to Assist in Epithelial Dysplasia Diagnosis
Karoline da Rocha, José C. M. Bermudez, Elena R. C. Rivero +1
The Epithelial Dysplasia (ED) is a tissue alteration commonly present in lesions preceding oral cancer, being its presence one of the most important factors in the progression towa…
Stochastic Analysis of the Diffusion Least Mean Square and Normalized Least Mean Square Algorithms for Cyclostationary White Gaussian and Non-Gaussian Inputs
Eweda Eweda, Neil J. Bershad, Jose C. M. Bermudez
The diffusion least mean square (DLMS) and the diffusion normalized least mean square (DNLMS) algorithms are analyzed for a network having a fusion center. This structure reduces t…
Graph topology inference with derivative-reproducing property in RKHS: algorithm and convergence analysis
Mircea Moscu, Ricardo A. Borsoi, Cédric Richard +1
In many areas such as computational biology, finance or social sciences, knowledge of an underlying graph explaining the interactions between agents is of paramount importance but…
Model-Based Deep Autoencoder Networks for Nonlinear Hyperspectral Unmixing
Haoqing Li, Ricardo Augusto Borsoi, Tales Imbiriba +3
Autoencoder (AEC) networks have recently emerged as a promising approach to perform unsupervised hyperspectral unmixing (HU) by associating the latent representations with the abun…
Fast Unmixing and Change Detection in Multitemporal Hyperspectral Data
Ricardo Augusto Borsoi, Tales Imbiriba, José Carlos Moreira Bermudez +1
Multitemporal spectral unmixing (SU) is a powerful tool to process hyperspectral image (HI) sequences due to its ability to reveal the evolution of materials over time and space in…
Tech Report: A Homogeneity-Based Multiscale Hyperspectral Image Representation for Sparse Spectral Unmixing
L. C. Ayres, S. J. M. de Almeida, J. C. M. Bermudez +1
Several approaches have been proposed to solve the spectral unmixing problem in hyperspectral image analysis. Among them the use of sparse regression techniques aims to characteriz…
Online Graph-Based Change Point Detection in Multiband Image Sequences
Ricardo Augusto Borsoi, Cédric Richard, André Ferrari +2
The automatic detection of changes or anomalies between multispectral and hyperspectral images collected at different time instants is an active and challenging research topic. To…
Coupled Tensor Decomposition for Hyperspectral and Multispectral Image Fusion with Inter-Image Variability
Ricardo Augusto Borsoi, Clémence Prévost, Konstantin Usevich +3
Coupled tensor approximation has recently emerged as a promising approach for the fusion of hyperspectral and multispectral images, reconciling state of the art performance with st…
Spectral Variability in Hyperspectral Data Unmixing: A Comprehensive Review
Ricardo Augusto Borsoi, Tales Imbiriba, José Carlos Moreira Bermudez +6
The spectral signatures of the materials contained in hyperspectral images, also called endmembers (EM), can be significantly affected by variations in atmospheric, illumination or…
Kalman Filtering and Expectation Maximization for Multitemporal Spectral Unmixing
Ricardo Augusto Borsoi, Tales Imbiriba, Pau Closas +2
The recent evolution of hyperspectral imaging technology and the proliferation of new emerging applications presses for the processing of multiple temporal hyperspectral images. In…
Deep Generative Models for Library Augmentation in Multiple Endmember Spectral Mixture Analysis
Ricardo Augusto Borsoi, Tales Imbiriba, José Carlos Moreira Bermudez +1
Multiple Endmember Spectral Mixture Analysis (MESMA) is one of the leading approaches to perform spectral unmixing (SU) considering variability of the endmembers (EMs). It represen…
A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing
Ricardo Augusto Borsoi, Tales Imbiriba, José Carlos Moreira Bermudez +1
Introducing spatial prior information in hyperspectral imaging (HSI) analysis has led to an overall improvement of the performance of many HSI methods applied for denoising, classi…
Deep Generative Endmember Modeling: An Application to Unsupervised Spectral Unmixing
Ricardo Augusto Borsoi, Tales Imbiriba, José Carlos Moreira Bermudez
Endmember (EM) spectral variability can greatly impact the performance of standard hyperspectral image analysis algorithms. Extended parametric models have been successfully applie…
Low-Rank Tensor Modeling for Hyperspectral Unmixing Accounting for Spectral Variability
Tales Imbiriba, Ricardo Augusto Borsoi, José Carlos Moreira Bermudez
Traditional hyperspectral unmixing methods neglect the underlying variability of spectral signatures often observed in typical hyperspectral images (HI), propagating these missmode…
Super-Resolution for Hyperspectral and Multispectral Image Fusion Accounting for Seasonal Spectral Variability
Ricardo Augusto Borsoi, Tales Imbiriba, José Carlos Moreira Bermudez
Image fusion combines data from different heterogeneous sources to obtain more precise information about an underlying scene. Hyperspectral-multispectral (HS-MS) image fusion is cu…
A Data Dependent Multiscale Model for Hyperspectral Unmixing With Spectral Variability
Ricardo Augusto Borsoi, Tales Imbiriba, José Carlos Moreira Bermudez
Spectral variability in hyperspectral images can result from factors including environmental, illumination, atmospheric and temporal changes. Its occurrence may lead to the propaga…
A Low-rank Tensor Regularization Strategy for Hyperspectral Unmixing
Tales Imbiriba, Ricardo Augusto Borsoi, José Carlos Moreira Bermudez
Tensor-based methods have recently emerged as a more natural and effective formulation to address many problems in hyperspectral imaging. In hyperspectral unmixing (HU), low-rank c…
Tech Report: A Fast Multiscale Spatial Regularization for Sparse Hyperspectral Unmixing
Ricardo Augusto Borsoi, Tales Imbiriba, José Carlos Moreira Bermudez +1
Sparse hyperspectral unmixing from large spectral libraries has been considered to circumvent limitations of endmember extraction algorithms in many applications. This strategy oft…
Generalized linear mixing model accounting for endmember variability
Tales Imbiriba, Ricardo Augusto Borsoi, José Carlos Moreira Bermudez
Endmember variability is an important factor for accurately unveiling vital information relating the pure materials and their distribution in hyperspectral images. Recently, the ex…
A New Adaptive Video Super-Resolution Algorithm With Improved Robustness to Innovations
Ricardo Augusto Borsoi, Guilherme Holsbach Costa, José Carlos Moreira Bermudez
In this paper, a new video super-resolution reconstruction (SRR) method with improved robustness to outliers is proposed. Although the R-LMS is one of the SRR algorithms with the b…
Super-Resolution Reconstruction of Electrical Impedance Tomography Images
Ricardo A. Borsoi, Julio C. C. Aya, Guilherme H. Costa +1
Electrical Impedance Tomography (EIT) systems are becoming popular because they present several advantages over competing systems. However, EIT leads to images with very low resolu…
Stochastic Behavior of the Nonnegative Least Mean Fourth Algorithm for Stationary Gaussian Inputs and Slow Learning
Jingen Ni, Jian Yang, Jie Chen +2
Some system identification problems impose nonnegativity constraints on the parameters to estimate due to inherent physical characteristics of the unknown system. The nonnegative l…
Nonparametric Detection of Nonlinearly Mixed Pixels and Endmember Estimation in Hyperspectral Images
Tales Imbiriba, José Carlos Moreira Bermudez, Cédric Richard +1
Mixing phenomena in hyperspectral images depend on a variety of factors such as the resolution of observation devices, the properties of materials, and how these materials interact…