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Author |
Victor Santos; Angel D. Sappa; Miguel Oliveira |
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Title |
Special Issue on Autonomous Driving an Driver Assistance Systems |
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2017 |
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In Robotics and Autonomous Systems Journal |
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Vol. 91 |
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pp. 208-209 |
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gtsi @ user @ |
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65 |
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Author |
Santos V.; Angel D. Sappa.; Oliveira M. & de la Escalera A. |
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Title |
Special Issue on Autonomous Driving and Driver Assistance Systems |
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Journal Article |
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2019 |
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In Robotics and Autonomous Systems |
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121 |
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gtsi @ user @ |
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119 |
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Author |
Rubio, G.A., Agila, W.E |
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Title |
A fuzzy model to manage water in polymer electrolyte membrane fuel cells |
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Journal Article |
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2021 |
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In Processes Journal. (Article number 904) |
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Vol. 9 |
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Issue 6 |
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PEM fuel cell, fuzzy, neural network, electrical response, flooding, drying. |
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In this paper, a fuzzy model is presented to determine in real-time the degree of dehydration or flooding of a proton exchange membrane of a fuel cell, to optimize its electrical response and consequently, its autonomous operation. By applying load, current and flux variations in the dry, normal, and flooded states of the membrane, it was determined that the temporal evolution of the fuel cell voltage is characterized by changes in slope and by its voltage oscillations. The results were validated using electrochemical impedance spectroscopy and show slope changes from 0.435 to 0.52 and oscillations from 3.6 mV to 5.2 mV in the dry state, and slope changes from 0.2 to 0.3 and oscillations from 1 mV to 2 mV in the flooded state. The use of fuzzy logic is a novelty and constitutes a step towards the progressive automation of the supervision, perception, and intelligent control of fuel cells, allowing them to reduce their risks and increase their economic benefits. |
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cidis @ cidis @ |
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153 |
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Santos, V., Sappa, A.D., Oliveira, M. & de la Escalera, A. |
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Editorial: Special Issue on Autonomous Driving and Driver Assistance Systems – Some Main Trends |
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Journal Article |
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2021 |
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In Journal: Robotics and Autonomous Systems. (Article number 103832) |
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Vol. 144 |
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cidis @ cidis @ |
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158 |
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Author |
Patricia Súarez, Henry Velesaca, Dario Carpio & Angel Sappa |
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Title |
Corn Kernel Classification From Few Training Samples |
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Journal Article |
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2023 |
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In journal Artificial Intelligence in Agriculture |
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Vol. 9 |
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pp. 89-99 |
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25897217 |
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no |
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cidis @ cidis @ |
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223 |
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Author |
Charco, J.L., Sappa, A.D., Vintimilla, B.X., Velesaca, H.O. |
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Title |
Camera pose estimation in multi-view environments:from virtual scenarios to the real world |
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Journal Article |
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Year |
2021 |
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In Image and Vision Computing Journal. (Article number 104182) |
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Vol. 110 |
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Relative camera pose estimation, Domain adaptation, Siamese architecture, Synthetic data, Multi-view environments |
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This paper presents a domain adaptation strategy to efficiently train network architectures for estimating the relative camera pose in multi-view scenarios. The network architectures are fed by a pair of simultaneously acquired
images, hence in order to improve the accuracy of the solutions, and due to the lack of large datasets with pairs of
overlapped images, a domain adaptation strategy is proposed. The domain adaptation strategy consists on transferring the knowledge learned from synthetic images to real-world scenarios. For this, the networks are firstly
trained using pairs of synthetic images, which are captured at the same time by a pair of cameras in a virtual environment; and then, the learned weights of the networks are transferred to the real-world case, where the networks are retrained with a few real images. Different virtual 3D scenarios are generated to evaluate the
relationship between the accuracy on the result and the similarity between virtual and real scenarios—similarity
on both geometry of the objects contained in the scene as well as relative pose between camera and objects in the
scene. Experimental results and comparisons are provided showing that the accuracy of all the evaluated networks for estimating the camera pose improves when the proposed domain adaptation strategy is used,
highlighting the importance on the similarity between virtual-real scenarios. |
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English |
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cidis @ cidis @ |
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147 |
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Author |
Velesaca, H.O., Suárez, P. L., Mira, R., & Sappa, A.D. |
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Title |
Computer Vision based Food Grain Classification: a Comprehensive Survey |
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Journal Article |
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2021 |
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In Computers and Electronics in Agriculture Journal. (Article number 106287) |
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Vol. 187 |
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cidis @ cidis @ |
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159 |
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Author |
Constantine Macías A., Toala Paz A., Realpe Miguel, Suárez Moncada Jenifer, Páez Rosas Diego & Jarrín Enrique Peláez |
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Leveraging Deep Learning Techniques for Marine and Coastal Wildlife Using Instance Segmentation: A Study on Galápagos Sea Lions |
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2024 |
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In 8th Ecuador Technical Chapters Meeting (ETCM 2024) Cuenca, October 15 – October 18, 2024 |
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cidis @ cidis @ |
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269 |
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Author |
Leo Ramos & Angel D. Sappa |
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Title |
Multispectral Semantic Segmentation for Land Cover Classification: An Overview |
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2024 |
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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Vol. 17 |
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14295-14336 |
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19391404 |
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cidis @ cidis @ |
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250 |
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Rato D., Oliveira M., Santos V., Sappa A. & Raducanu B. |
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Title |
Multi-View 2D to 3D Lifting Video-Based Optimization: A Robust Approach for Human Pose Estimation with Occluded Joint Prediction |
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2024 |
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IEEE Int. Conf. on Intelligent Robots and Systems (IROS), Abu Dhabi, October 14-18, 2024 |
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cidis @ cidis @ |
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255 |
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