most citedReal-time Convolutional Neural Networks for Emotion and Gender Classification

60 citations · 70 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2020

Unsupervised Difficulty Estimation with Action Scores

Octavio Arriaga, Matias Valdenegro-Toro

Evaluating difficulty and biases in machine learning models has become of extreme importance as current models are now being applied in real-world situations. In this paper we pres…

cs.CV2020

Black-Box Optimization of Object Detector Scales

Mohandass Muthuraja, Octavio Arriaga, Paul Plöger +2

Object detectors have improved considerably in the last years by using advanced CNN architectures. However, many detector hyper-parameters are generally manually tuned, or they are…

cs.CV20206 cited

Perception for Autonomous Systems (PAZ)

Octavio Arriaga, Matias Valdenegro-Toro, Mohandass Muthuraja +2

In this paper we introduce the Perception for Autonomous Systems (PAZ) software library. PAZ is a hierarchical perception library that allow users to manipulate multiple levels of…

cs.CV20174 cited

Image Captioning and Classification of Dangerous Situations

Octavio Arriaga, Paul Plöger, Matias Valdenegro-Toro

Current robot platforms are being employed to collaborate with humans in a wide range of domestic and industrial tasks. These environments require autonomous systems that are able…

cs.CV201760 cited

Real-time Convolutional Neural Networks for Emotion and Gender Classification

Octavio Arriaga, Matias Valdenegro-Toro, Paul Plöger

In this paper we propose an implement a general convolutional neural network (CNN) building framework for designing real-time CNNs. We validate our models by creating a real-time v…