Publications

2018

• Barros, P., Barakova, E., & Wermter, S. (2018). A Deep Neural Model Of Emotion Appraisal. arXiv preprint arXiv:1808.00252.
• Parisi, G.,Barros, P., Fu, D., Liu, X., Wertmer, S. A Neurorobotic Experiment for Crossmodal Conflict Resolution in Complex Environments. Accepted at IROS 2018.
• Churamani, N., Sutherland, A., Barros, P. An Affective Robot Companion for Assisting the Elderly in a Cognitive Game Scenario. Proceedings of the Workshop on Intelligent Assistive Computing, IEEE World Congress on Computational Intelligence (WCCI) 2018.
• Barros, P., Churamani, N., Lakomkin, E., Siqueira, H., Sutherland, A., & Wermter, S. (2018, July). The OMG-Emotion Behavior Dataset. In Neural Networks (IJCNN), 2018 International Joint Conference on (pp. 1408-1414). IEEE.
• Barros, P., Parisi, G., Fu, D., Liu, X., Wertmer, S. (2018, July). Expectation Learning and Crossmodal Modulation with a Deep Adversarial Network. In Neural Networks (IJCNN), 2018 International Joint Conference on (pp. 5314-5321). IEEE.
• Churamani, N., Barros, P., Strahl, E., & Wermter, S. (2018, July). Learning Empathy-Driven Emotion Expressions using Affective Modulations. In Neural Networks (IJCNN), 2018 International Joint Conference on (pp. 1400-1407). IEEE.
• Siqueira, H., Barros, P., Magg, S., Weber, C., & Wermter, S. A Sub-Layered Hierarchical Pyramidal Neural Architecture for Facial Expression Recognition.In Proceedings of the European symposium on artificial neural networks computational intelligence and machine learning (ESANN) (pp. 1-6).

2017

• Lima, T., Fernandes, B., & Barros, P. (2017, November). Human action recognition with 3D convolutional neural network. In Computational Intelligence (LA-CCI), 2017 IEEE Latin American Conference on (pp. 1-6). IEEE.
• Ferreira, J., Ferro, M., Fernandes, B., Valenca, M., Bastos-Filho, C., & Barros, P. (2017, November). Extreme learning machine autoencoder for data augmentation. In Computational Intelligence (LA-CCI), 2017 IEEE Latin American Conference on (pp. 1-6). IEEE.
• Parisi, G. I., Barros, P., Kerzel, M., Wu, H., Yang, G., Li, Z., … & Wermter, S. (2017). A computational model of crossmodal processing for conflict resolution. In IEEE International Conference on Development and Learning and on Epigenetic Robotics (EPIROB-ICDL). IEEE (pp. 33-38).
• P Barros, GI Parisi, D Fu, X Liu, S Wermter. Expectation Learning for Adaptive Crossmodal Stimuli Association. EUCog Meeting, 2017
• Elfaramawy, N., Barros, P., Parisi, G. I., & Wermter, S. (2017, October). Emotion Recognition from Body Expressions with a Neural Network Architecture. In Proceedings of the 5th International Conference on Human Agent Interaction (pp. 143-149). ACM.
• Barros, P., Parisi, G. I., Weber, C., & Wermter, S. (2017). Emotion-modulated attention improves expression recognition: A deep learning model. Neurocomputing, 253, 104-114.
• Barros, P., & Wermter, S. (2017, May). A self-organizing model for affective memory. In Neural Networks (IJCNN), 2017 International Joint Conference on (pp. 31-38). IEEE.
• Churamani, N., Kerzel, M., Strahl, E., Barros, P., & Wermter, S. (2017, May). Teaching emotion expressions to a human companion robot using deep neural architectures. In Neural Networks (IJCNN), 2017 International Joint Conference on (pp. 627-634). IEEE.
• Tsironi, E., Barros, P., Weber, C., & Wermter, S. (2017). An analysis of Convolutional Long Short-Term Memory Recurrent Neural Networks for gesture recognition. Neurocomputing.
• Barros, P., Maciel-Junior, N. T., Fernandes, B. J., Bezerra, B. L., & Fernandes, S. M. (2017). A dynamic gesture recognition and prediction system using the convexity approach. Computer Vision and Image Understanding, 155, 139-149.

2016

• Barros, P., & Wermter, S. (2016). Developing crossmodal expression recognition based on a deep neural model. Adaptive behavior, 24(5), 373-396.
• Hinz, T., Barros, P., & Wermter, S. (2016, September). The Effects of Regularization on Learning Facial Expressions with Convolutional Neural Networks. In International Conference on Artificial Neural Networks (pp. 80-87). Springer International Publishing.
• Barros, P., Weber, C., & Wermter, S. (2016, July). Learning auditory neural representations for emotion recognition. In Neural Networks (IJCNN), 2016 International Joint Conference on (pp. 921-928). IEEE.
• Mousavi, N., Siqueira, H., Barros, P., Fernandes, B., & Wermter, S. (2016, July). Understanding how deep neural networks learn face expressions. In Neural Networks (IJCNN), 2016 International Joint Conference on (pp. 227-234). IEEE.
• Tsironi, E., Barros, P., & Wermter, S. (2016). Gesture recognition with a convolutional long short-term memory recurrent neural network. In Proceedings of the European symposium on artificial neural networks computational intelligence and machine learning (ESANN) (pp. 213-218).
• Speck, D., Barros, P., Weber, C., & Wermter, S. (2016). Ball localization for robocup soccer using convolutional neural networks. In Proceedings of the 2016 RoboCup International Symposium (RoboCup’2016).

2015

• Barros, P., Jirak, D., Weber, C., & Wermter, S. (2015). Multimodal emotional state recognition using sequence-dependent deep hierarchical features. Neural Networks, 72, 140-151.
• Barros, P., Weber, C., & Wermter, S. (2015, November). Emotional expression recognition with a cross-channel convolutional neural network for human-robot interaction. In Humanoid Robots (Humanoids), 2015 IEEE-RAS 15th International Conference on (pp. 582-587). IEEE.
• Barros, P., & Wermter, S. (2015, September). Recognizing complex mental states with deep hierarchical features for Human-Robot Interaction. In Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International Conference on (pp. 4065-4070). IEEE.
• Hamester, D., Barros, P., & Wermter, S. (2015, July). Face expression recognition with a 2-channel convolutional neural network. In Neural Networks (IJCNN), 2015 International Joint Conference on (pp. 1-8). IEEE.
• Jirak, D., Barros, P., & Wermter, S. (2015). Dynamic gesture recognition using echo state networks. In Proceedings (Vol. 475). Presses universitaires de Louvain.
• Soares, M. B., Barros, P., Parisi, G. I., & Wermter, S. (2015). Learning objects from rgb-d sensors using point cloud-based neural networks. In 23th European Symposium on Artifical Neural Networks, Computational Intelligence and Machine Learning. Bruges (pp. 439-444).

2014

• Barros, P., Parisi, G. I., Jirak, D., & Wermter, S. (2014, November). Real-time gesture recognition using a humanoid robot with a deep neural architecture. In Humanoid Robots (Humanoids), 2014 14th IEEE-RAS International Conference on (pp. 646-651). IEEE.
• Barros, P., Magg, S., Weber, C., & Wermter, S. (2014, September). A multichannel convolutional neural network for hand posture recognition. In International Conference on Artificial Neural Networks (pp. 403-410). Springer, Cham.
• Soares, M. B., Barros, P., & Wermter, S. (2014, August). Learning Objects From RGB-D Sensors for Cleaning Tasks Using a Team of Cooperative Humanoid Robots. In Advances in Autonomous Robotics Systems: 15th Annual Conference, TAROS 2014, Birmingham, UK, September 1-3, 2014. Proceedings (Vol. 8717, p. 273). Springer.
• Parisi, G. I., Barros, P., & Wermter, S. (2014). FINGeR: Framework for interactive neural-based gesture recognition. In ESANN.

2013

• Barros, P. V., Júnior, N. T., Bisneto, J. M., Fernandes, B. J., Bezerra, B. L., & Fernandes, S. M. (2013, September). An effective dynamic gesture recognition system based on the feature vector reduction for SURF and LCS. In International Conference on Artificial Neural Networks (pp. 412-419). Springer, Berlin, Heidelberg.
• Junior, N. T., Barros, P. V., Fernandes, B. J., Bezerra, B. L., & Fernandes, S. M. (2013, September). A Dynamic Gesture Prediction System Based on the CLCS Feature Extraction. In Computational Intelligence and 11th Brazilian Congress on Computational Intelligence (BRICS-CCI & CBIC), 2013 BRICS Congress on (pp. 501-506). IEEE.
• Barros, P. V., Junior, N., Bisneto, J. M., Fernandes, B. J., Bezerra, B. L., & Fernandes, S. M. (2013, March). Convexity local contour sequences for gesture recognition. In Proceedings of the 28th Annual ACM Symposium on Applied Computing (pp. 34-39). ACM.

2011

• Barros, P. , Projeto PaNDA: Um framework semântico para geração de sistemas. 2011. Trabalho de Conclusão de Curso (Graduação em Sistema de Informações) – Universidade Federal Rural de Pernambuco.