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Gisel Bastidas G., P. M. V., Boris Vintimilla & Angel D. Sappa. (2025). Application-Guided Image Fusion: A Path to Improve Results in High-Level Vision Tasks. 20th International Conference on Computer Vision Theory and Applications VISAPP 2025, .
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Henry O. Velesaca, A. D. S. & J. A. H. (2025). A Case Study of Anomaly Detection in Tinplate Lids: Supervised vs Unsupervised approaches. 11th International Conference on Automation, Robotics, and Applications (ICARA 2025), .
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Henry O. Velesaca & Angel D. Sappa. (2025). Seeing the Unseen: AI-Powered Camouflaged Pest Detection. 9th International Conference on Machine Vision and Information Technology (CMVIT 2025), .
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Constantine Macías A., T. P. A., Realpe Miguel, Suárez Moncada Jenifer, Páez Rosas Diego & Jarrín Enrique Peláez. (2024). Leveraging Deep Learning Techniques for Marine and Coastal Wildlife Using Instance Segmentation: A Study on Galápagos Sea Lions. In 8th Ecuador Technical Chapters Meeting (ETCM 2024) Cuenca, October 15 – October 18, 2024, .
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Leo Thomas Ramos & Angel D. Sappa. (2025). Leveraging U-Net and selective feature extraction for land cover classification using remote sensing imagery. Scientific Reports, .
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Leo Thomas Ramos & Angel D. Sappa. (2025). Dual-branch ConvNeXt-based Network with Attentional Fusion Decoding for Land Cover Classification Using Multispectral Imagery. In IEEE SoutheastCon 2025.
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Leo Thomas Ramos & Angel D. Sappa. (2025). Enhanced Aerial Scene Classification Through ConvNeXt Architectures and Channel Attention. In 10th International Congress on Information and Communication Technology.
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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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Jorge Alvarez Tello, Mireya Zapata, & Dennys Paillacho. (2019). Kinematic optimization of a robot head movements for the evaluation of human-robot interaction in social robotics. In 10th International Conference on Applied Human Factors and Ergonomics and the Affiliated Conferences (AHFE 2019), Washington D.C.; United States. Advances in Intelligent Systems and Computing (Vol. 975, pp. 108–118).
Abstract: This paper presents the simplification of the head movements from
the analysis of the biomechanical parameters of the head and neck at the
mechanical and structural level through CAD modeling and construction with
additive printing in ABS/PLA to implement non-verbal communication strategies and establish behavior patterns in the social interaction. This is using in the
denominated MASHI (Multipurpose Assistant robot for Social Human-robot
Interaction) experimental robotic telepresence platform, implemented by a
display with a fish-eye camera along with the mechanical mechanism, which
permits 4 degrees of freedom (DoF). In the development of mathematicalmechanical modeling for the kinematics codification that governs the robot and
the autonomy of movement, we have the Pitch, Roll, and Yaw movements, and
the combination of all of them to establish an active communication through
telepresence. For the computational implementation, it will be show the rotational matrix to describe the movement.
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Shendry Rosero Vásquez. (2019). Reconocimiento facial: técnicas tradicionales y técnicas de aprendizaje profundo, un análisis. (Ph.D. Angel Sappa, Director & Ph.D. Boris Vintimilla, Codirector.). M.Sc. thesis. In Ediciones FIEC-ESPOL.
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