3 citations · 4 across the 10 of their papers we have counts for
5 papers · 1 filter
Deep Feedback Models
David Calhas, Arlindo L. Oliveira
Deep Feedback Models (DFMs) are a new class of stateful neural networks that combine bottom up input with high level representations over time. This feedback mechanism introduces d…
Deep Recurrence for Dynamical Segmentation Models
David Calhas, Arlindo L. Oliveira
While biological vision systems rely heavily on feedback connections to iteratively refine perception, most artificial neural networks remain purely feedforward, processing input i…
Are ECGs enough? Deep learning classification of pulmonary embolism using electrocardiograms
Joao D. S. Marques, Arlindo L. Oliveira
Pulmonary embolism is a leading cause of out of hospital cardiac arrest that requires fast diagnosis. While computed tomography pulmonary angiography is the standard diagnostic too…
DIS-CO: Discovering Copyrighted Content in VLMs Training Data
André V. Duarte, Xuandong Zhao, Arlindo L. Oliveira +1
How can we verify whether copyrighted content was used to train a large vision-language model (VLM) without direct access to its training data? Motivated by the hypothesis that a V…
The Role of Recurrency in Image Segmentation for Noisy and Limited Sample Settings
David Calhas, João Marques, Arlindo L. Oliveira
The biological brain has inspired multiple advances in machine learning. However, most state-of-the-art models in computer vision do not operate like the human brain, simply becaus…