10 papers
Fourier fractal dimension to predict the generalization of deep neural networks
Joao B. Florindo, Davi Wanderley Misturini
Predicting the generalization performance of deep neural networks without relying on hold-out validation data is a fundamental challenge in machine learning. While Stochastic Gradi…
A self-supervised learning approach to deep filter banks for texture recognition
Joao B. Florindo, Lucas O. Lyra, Antonio E. Fabris
An important challenge in texture recognition is the limited amount of data for training frequently found in real-world applications. In computer vision in general, a successful st…
Sleep-stage efficient classification using a lightweight self-supervised model
Eldiane Borges dos Santos Durães, João Batista Florindo
Accurate classification of sleep stages is crucial for diagnosing sleep disorders and automating this process can significantly enhance clinical assessments. This study aims to exp…
A multifractal-based masked auto-encoder: an application to medical images
Joao Batista Florindo, Viviane de Moura
Masked autoencoders (MAE) have shown great promise in medical image classification. However, the random masking strategy employed by traditional MAEs may overlook critical areas in…
ConvNeXt-FD: A Fractal-Based Deep Model for Robust Biomedical Image Segmentation
Joao Batista Florindo, Amanda Pontes de Oliveira Ornelas
Biomedical image segmentation is a critical task in medical diagnosis and treatment planning, enabling precise delineation of anatomical structures and pathological regions. Despit…
Entropy-Guided Self-Supervised Learning for Medical Image Classification
Joao Florindo, Viviane Moura
Accurate and robust medical image classification is paramount for early disease diagnosis and treatment planning. However, challenges such as limited annotated data, high intra-cla…
Chaotic Contrastive Learning for Robust Texture Classification
Joao B Florindo
Texture classification is a pivotal task in computer vision, presenting unique challenges due to high inter-class similarity and the sensitivity of structural patterns to scale and…
Attention-Based Chaotic Self-Supervision for Medical Image Classification
Joao Batista Florindo, Amanda Pontes de Oliveira Ornelas
Deep learning models for medical image classification usually achieve promising results but typically rely on large, annotated datasets or standard transfer learning from ImageNet.…
Deep neural networks with Fisher vector encoding for medical image classification
Lucas O. Lyra, Antonio E. Fabris, Joao B. Florindo
Orderless encoding methods have shown to improve Convolutional Neural Networks (CNNs) for image classification in the context of limited availability of data. Additionally, hybrid…
Approximating Condorcet Ordering for Vector-valued Mathematical Morphology
Marcos Eduardo Valle, Santiago Velasco-Forero, Joao Batista Florindo +1
Mathematical morphology provides a nonlinear framework for image and spatial data processing and analysis. Although there have been many successful applications of mathematical mor…