81 citations · 92 across the 5 of their papers we have counts for
8 papers
When Layers Play the Lottery, all Tickets Win at Initialization
Artur Jordao, George Correa de Araujo, Helena de Almeida Maia +1
Pruning is a standard technique for reducing the computational cost of deep networks. Many advances in pruning leverage concepts from the Lottery Ticket Hypothesis (LTH). LTH revea…
On the Effect of Pruning on Adversarial Robustness
Artur Jordao, Helio Pedrini
Pruning is a well-known mechanism for reducing the computational cost of deep convolutional networks. However, studies have shown the potential of pruning as a form of regularizati…
Stage-Wise Neural Architecture Search
Artur Jordao, Fernando Akio, Maiko Lie +1
Modern convolutional networks such as ResNet and NASNet have achieved state-of-the-art results in many computer vision applications. These architectures consist of stages, which ar…
Covariance-free Partial Least Squares: An Incremental Dimensionality Reduction Method
Artur Jordao, Maiko Lie, Victor Hugo Cunha de Melo +1
Dimensionality reduction plays an important role in computer vision problems since it reduces computational cost and is often capable of yielding more discriminative data represent…
Pruning Deep Neural Networks using Partial Least Squares
Artur Jordao, Ricardo Kloss, Fernando Yamada +1
Modern pattern recognition methods are based on convolutional networks since they are able to learn complex patterns that benefit the classification. However, convolutional network…
A Content-Based Late Fusion Approach Applied to Pedestrian Detection
Jessica Sena, Artur Jordao, William Robson Schwartz
The variety of pedestrians detectors proposed in recent years has encouraged some works to fuse pedestrian detectors to achieve a more accurate detection. The intuition behind is t…
Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-Art
Artur Jordao, Antonio C. Nazare, Jessica Sena +1
Human activity recognition based on wearable sensor data has been an attractive research topic due to its application in areas such as healthcare and smart environments. In this co…
Latent hypernet: Exploring all Layers from Convolutional Neural Networks
Artur Jordao, Ricardo Kloss, William Robson Schwartz
Since Convolutional Neural Networks (ConvNets) are able to simultaneously learn features and classifiers to discriminate different categories of activities, recent works have emplo…