Pablo Zegers

Orcid: 0000-0003-3697-2525

According to our database1, Pablo Zegers authored at least 30 papers between 2000 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

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Bibliography

2022
Video-based Human Action Recognition using Deep Learning: A Review.
CoRR, 2022

2020
A Unified Deep Framework for Joint 3D Pose Estimation and Action Recognition from a Single RGB Camera.
Sensors, 2020

2019
Spatio-Temporal Image Representation of 3D Skeletal Movements for View-Invariant Action Recognition with Deep Convolutional Neural Networks.
Sensors, 2019

Learning to recognise 3D human action from a new skeleton-based representation using deep convolutional neural networks.
IET Comput. Vis., 2019

A Unified Deep Framework for Joint 3D Pose Estimation and Action Recognition from a Single RGB Camera.
CoRR, 2019

A Deep Learning Approach for Real-Time 3D Human Action Recognition from Skeletal Data.
CoRR, 2019

A Deep Learning Approach for Real-Time 3D Human Action Recognition from Skeletal Data.
Proceedings of the Image Analysis and Recognition - 16th International Conference, 2019

2018
Exploiting Spatio-Temporal Structure With Recurrent Winner-Take-All Networks.
IEEE Trans. Neural Networks Learn. Syst., 2018

Exploiting deep residual networks for human action recognition from skeletal data.
Comput. Vis. Image Underst., 2018

Learning to Recognize 3D Human Action from A New Skeleton-based Representation Using Deep Convolutional Neural Networks.
CoRR, 2018

Exploiting deep residual networks for human action recognition from skeletal data.
CoRR, 2018

Learning and Recognizing Human Action from Skeleton Movement with Deep Residual Neural Networks.
CoRR, 2018

Skeletal Movement to Color Map: A Novel Representation for 3D Action Recognition with Inception Residual Networks.
Proceedings of the 2018 IEEE International Conference on Image Processing, 2018

2016
Information Theoretical Measures for Achieving Robust Learning Machines.
Entropy, 2016

People Counting in Videos by Fusing Temporal Cues from Spatial Context-Aware Convolutional Neural Networks.
Proceedings of the Computer Vision - ECCV 2016 Workshops, 2016

2015
Fisher Information Properties.
Entropy, 2015

2014
A Novel, Fully Automated Pipeline for Period Estimation in the EROS 2 Data Set.
CoRR, 2014

Computational Intelligence Challenges and Applications on Large-Scale Astronomical Time Series Databases.
IEEE Comput. Intell. Mag., 2014

2013
Relative Entropy Derivative Bounds.
Entropy, 2013

2012
An Information Theoretic Algorithm for Finding Periodicities in Stellar Light Curves.
IEEE Trans. Signal Process., 2012

2011
Period Estimation in Astronomical Time Series Using Slotted Correntropy.
IEEE Signal Process. Lett., 2011

2010
Period detection in light curves from astronomical objects using correntropy.
Proceedings of the International Joint Conference on Neural Networks, 2010

2009
Bounded-time system identification under neuro-sliding training.
Proceedings of the International Joint Conference on Neural Networks, 2009

2007
Boosting Learning Machines with Function Compositions to Avoid Local Minima in Regression Problems.
Proceedings of the International Joint Conference on Neural Networks, 2007

2006
Exponential Transitions: Telltale Sign of Consistency in Learning Systems.
Proceedings of the International Joint Conference on Neural Networks, 2006

Consistent Density Function Estimation with Multilayer Perceptrons.
Proceedings of the International Joint Conference on Neural Networks, 2006

Semi-Autonomous Neural Networks Differential Equation Solver.
Proceedings of the International Joint Conference on Neural Networks, 2006

2003
Trajectory generation and modulation using dynamic neural networks.
IEEE Trans. Neural Networks, 2003

2002
Determining The Degree of Generalization Using An Incremental Learning Algorithm.
Proceedings of the Soft Computing Systems - Design, Management and Applications, 2002

2000
Periodic Motions, Mapping Ordered Sequences, and Training of Dynamic Neural Networks to Generate Continuous and Discontinuous Trajectories.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000


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