24 citations · 27 across the 5 of their papers we have counts for
8 papers
Large-Margin Representation Learning for Texture Classification
Jonathan de Matos, Luiz Eduardo Soares de Oliveira, Alceu de Souza Britto Junior +1
This paper presents a novel approach combining convolutional layers (CLs) and large-margin metric learning for training supervised models on small datasets for texture classificati…
Multiscale Analysis for Improving Texture Classification
Steve T. M. Ataky, Diego Saqui, Jonathan de Matos +2
Information from an image occurs over multiple and distinct spatial scales. Image pyramid multiresolution representations are a useful data structure for image analysis and manipul…
Machine Learning Methods for Histopathological Image Analysis: A Review
Jonathan de Matos, Steve Tsham Mpinda Ataky, Alceu de Souza Britto +2
Histopathological images (HIs) are the gold standard for evaluating some types of tumors for cancer diagnosis. The analysis of such images is not only time and resource consuming,…
Data Augmentation for Histopathological Images Based on Gaussian-Laplacian Pyramid Blending
Steve Tsham Mpinda Ataky, Jonathan de Matos, Alceu de S. Britto +2
Data imbalance is a major problem that affects several machine learning (ML) algorithms. Such a problem is troublesome because most of the ML algorithms attempt to optimize a loss…
Texture CNN for Histopathological Image Classification
Jonathan de Matos, Alceu de S. Britto, Luiz E. S. de Oliveira +1
Biopsies are the gold standard for breast cancer diagnosis. This task can be improved by the use of Computer Aided Diagnosis (CAD) systems, reducing the time of diagnosis and reduc…
A Novel Orthogonal Direction Mesh Adaptive Direct Search Approach for SVM Hyperparameter Tuning
Alexandre Reeberg Mello, Jonathan de Matos, Marcelo R. Stemmer +2
In this paper, we propose the use of a black-box optimization method called deterministic Mesh Adaptive Direct Search (MADS) algorithm with orthogonal directions (Ortho-MADS) for t…