3 papers
cs.LG2026
Silhouette Loss: Differentiable Global Structure Learning for Deep Representations
Matheus Vinícius Todescato, Joel Luís Carbonera
Learning discriminative representations is a central goal of supervised deep learning. While cross-entropy (CE) remains the dominant objective for classification, it does not expli…
cs.CV2025
No Labels Needed: Zero-Shot Image Classification with Collaborative Self-Learning
Matheus Vinícius Todescato, Joel Luís Carbonera
While deep learning, including Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs), has significantly advanced classification performance, its typical reliance on e…
cs.LG2025
An approach based on class activation maps for investigating the effects of data augmentation on neural networks for image classification
Lucas M. Dorneles, Luan Fonseca Garcia, Joel Luís Carbonera
Neural networks have become increasingly popular in the last few years as an effective tool for the task of image classification due to the impressive performance they have achieve…