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Patricia L. Suárez, A. D. S. and B. X. V. (2021). Deep learning-based vegetation index estimation. In Generative Adversarial Networks for Image-to-Image Translation Book. (Vol. Chapter 9, pp. 205–232).
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Dennis G. Romero, A. F. N., & Teodiano Freire B. (2014). Reconocimiento en-línea de acciones humanas basado en patrones de RWE aplicado en ventanas dinámicas de momentos invariantes. Revista Iberoamericana de Automática e Informática industrial 00 (2014), Vol. 11, pp. 202–211.
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Cristhian A. Aguilera, Angel D. Sappa, & R. Toledo. (2015). LGHD: A feature descriptor for matching across non-linear intensity variations. In IEEE International Conference on, Quebec City, QC, 2015 (pp. 178–181). Quebec City, QC, Canada: IEEE.
Abstract: This paper presents a new feature descriptor suitable to the task of matching features points between images with nonlinear intensity variations. This includes image pairs with significant illuminations changes, multi-modal image pairs and multi-spectral image pairs. The proposed method describes the neighbourhood of feature points combining frequency and spatial information using multi-scale and multi-oriented Log- Gabor filters. Experimental results show the validity of the proposed approach and also the improvements with respect to the state of the art.
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Patricia L. Suárez, D. C., and Angel Sappa. (2021). Non-Homogeneous Haze Removal through a Multiple Attention Module Architecture. In 16 International Symposium on Visual Computing. Octubre 4-6, 2021. Lecture Notes in Computer Science (Vol. 13018, pp. 178–190).
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Viñán-Ludeña, M. S., Roberto Jacome Galarza, Montoya, L.R., Leon, A.V., & Ramírez, C.C. (2020). Smart university: an architecture proposal for information management using open data for research projects. Advances in Intelligent Systems and Computing, 1137 AISC, 2020, 172–178.
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Luis C. Herrera, L. del R. L., Nayeth I. Solorzano, Jonathan S. Paillacho & Dennys Paillacho. (2021). Metrics Design of Usability and Behavior Analysis of a Human-Robot-Game Platform. In The 2nd International Conference on Applied Technologies (ICAT 2020), diciembre 2-4. Communication in Computer and Information Science (Vol. 1388, pp. 164–178).
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Jorge Alvarez, Mireya Zapata, & Dennys Paillacho. (2019). Mechanical Design of a spatial mechanism for the robot head movements in social robotics for the evaluation of Human-Robot Interaction. In 2nd International Conference on Human Systems Engineering and Design: Future Trends and Applications (IHSED 2019); Munich, Alemania (Vol. 1026, pp. 160–165).
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Cristina L. Abad, Yi Lu, & Roy H. Campbell. (2011). DARE: Adaptive Data Replication for Efficient Cluster Scheduling. In IEEE International Conference on Cluster Computing, 2011 (pp. 159–168).
Abstract: Placing data as close as possible to computation is a common practice of data intensive systems, commonly referred to as the data locality problem. By analyzing existing production systems, we confirm the benefit of data locality and find that data have different popularity and varying correlation of accesses. We propose DARE, a distributed adaptive data replication algorithm that aids the scheduler to achieve better data locality. DARE solves two problems, how many replicas to allocate for each file and where to place them, using probabilistic sampling and a competitive aging algorithm independently at each node. It takes advantage of existing remote data accesses in the system and incurs no extra network usage. Using two mixed workload traces from Facebook, we show that DARE improves data locality by more than 7 times with the FIFO scheduler in Hadoop and achieves more than 85% data locality for the FAIR scheduler with delay scheduling. Turnaround time and job slowdown are reduced by 19% and 25%, respectively.
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Cristhian A. Aguilera, Xaver Soria, Angel D. Sappa, & Ricardo Toledo. (2017). RGBN Multispectral Images: a Novel Color Restoration Approach. In 15th International Conference on Practical Applications of Agents and Multi-Agent Systems (Vol. 619, pp. 155–163).
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M. Diaz, Dennys Paillacho, C. Angulo, O. Torres, J. Gonzálalez, & J. Albo Canals. (2014). A Week-long Study on Robot-Visitors Spatial Relationships during Guidance in a Sciences Museum. In ACM/IEEE International Conference on Human-Robot Interaction (pp. 152–153).
Abstract: In order to observe spatial relationships in social human- robot interactions, a field trial was carried out within the CosmoCaixa Science Museum in Barcelona. The follow me episodes studied showed that the space configurations formed by guide and visitors walking together did not always fit the robot social affordances and navigation requirements to perform the guidance successfully, thus additional commu- nication prompts are considered to regulate effectively the walking together and follow me behaviors.
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