8 citations · 8 across the 3 of their papers we have counts for
3 papers
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…
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…
An evaluation of pre-trained models for feature extraction in image classification
Erick da Silva Puls, Matheus V. Todescato, Joel L. Carbonera
In recent years, we have witnessed a considerable increase in performance in image classification tasks. This performance improvement is mainly due to the adoption of deep learning…