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| Author | W. Agila; Gomer Rubio; L. Miranda; D. Sanaguano | ||||
| Title | Open Control Architecture for the Characterization and Control of the PEM Fuel Cell | Type | Conference Article | ||
| Year | 2019 | Publication | IEEE ETCM 2019 Fourth Ecuador Technical Chapters Meeting; Guayaquil, Ecuador | Abbreviated Journal | |
| Volume | Issue | Pages  |
1-5 | ||
| Keywords | PEM fuel cell, Experimental System, Control Engineering. | ||||
| Abstract | Proton exchange membrane (PEM) fuel cells, are an efficient and clean source of electrical energy. The analysis of its operation requires experimental work, which allows measuring, modeling and optimizing PEM fuel cells electrical behavior under different operating conditions. Therefore, having an experimentation platform that allows to easily carry out its study and control is essential. This research presents the design and development of an open instrumental system that allows measuring, controlling and determining the operating parameters of a PEM fuel cell. As results, the polarization curves, voltage-current, obtained by the system itself in different experimental conditions are shown. These curves are a very useful tool to evaluate the electrical behavior of the PEM battery. | ||||
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| Notes | Approved | no | |||
| Call Number | gtsi @ user @ | Serial | 118 | ||
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| Author | Cristhian A. Aguilera, Cristhian Aguilera, Cristóbal A. Navarro, & Angel D. Sappa | ||||
| Title | Fast CNN Stereo Depth Estimation through Embedded GPU Devices | Type | Journal Article | ||
| Year | 2020 | Publication | Sensors 2020 | Abbreviated Journal | |
| Volume | Vol. 2020-June | Issue | 11 | Pages |
pp. 1-13 |
| Keywords | stereo matching; deep learning; embedded GPU | ||||
| Abstract | Current CNN-based stereo depth estimation models can barely run under real-time constraints on embedded graphic processing unit (GPU) devices. Moreover, state-of-the-art evaluations usually do not consider model optimization techniques, being that it is unknown what is the current potential on embedded GPU devices. In this work, we evaluate two state-of-the-art models on three different embedded GPU devices, with and without optimization methods, presenting performance results that illustrate the actual capabilities of embedded GPU devices for stereo depth estimation. More importantly, based on our evaluation, we propose the use of a U-Net like architecture for postprocessing the cost-volume, instead of a typical sequence of 3D convolutions, drastically augmenting the runtime speed of current models. In our experiments, we achieve real-time inference speed, in the range of 5–32 ms, for 1216 368 input stereo images on the Jetson TX2, Jetson Xavier, and Jetson Nano embedded devices. |
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| Language | English | Summary Language | English | Original Title | |
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| ISSN | 14248220 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 132 | ||
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| Author | Ángel Morera, Ángel Sánchez, A. Belén Moreno, Angel D. Sappa, & José F. Vélez | ||||
| Title | SSD vs. YOLO for Detection of Outdoor Urban Advertising Panels under Multiple Variabilities. | Type | Journal Article | ||
| Year | 2020 | Publication | Abbreviated Journal | In Sensors | |
| Volume | Vol. 2020-August | Issue | 16 | Pages |
pp. 1-23 |
| Keywords | object detection; urban outdoor panels; one-stage detectors; Single Shot MultiBox Detector (SSD); You Only Look Once (YOLO); detection metrics; object and scene imaging variabilities | ||||
| Abstract | This work compares Single Shot MultiBox Detector (SSD) and You Only Look Once (YOLO) deep neural networks for the outdoor advertisement panel detection problem by handling multiple and combined variabilities in the scenes. Publicity panel detection in images o ers important advantages both in the real world as well as in the virtual one. For example, applications like Google Street View can be used for Internet publicity and when detecting these ads panels in images, it could be possible to replace the publicity appearing inside the panels by another from a funding company. In our experiments, both SSD and YOLO detectors have produced acceptable results under variable sizes of panels, illumination conditions, viewing perspectives, partial occlusion of panels, complex background and multiple panels in scenes. Due to the diculty of finding annotated images for the considered problem, we created our own dataset for conducting the experiments. The major strength of the SSD model was the almost elimination of False Positive (FP) cases, situation that is preferable when the publicity contained inside the panel is analyzed after detecting them. On the other side, YOLO produced better panel localization results detecting a higher number of True Positive (TP) panels with a higher accuracy. Finally, a comparison of the two analyzed object detection models with di erent types of semantic segmentation networks and using the same evaluation metrics is also included. |
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| Language | English | Summary Language | English | Original Title | |
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| ISSN | ISBN | 14248220 | Medium | ||
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 133 | ||
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| Author | Rafael Rivadeneira, Henry Velesaca & Angel Sappa | ||||
| Title | Cross-Spectral Image Registration: a Comparative Study and a New Benchmark Dataset | Type | Conference Article | ||
| Year | 2024 | Publication | Lecture Notes in Networks and Systems: 4th International Conference on Innovations in Computational Intelligence and Computer Vision (ICICV 2024) | Abbreviated Journal | |
| Volume | Vol. 1117 LNNS | Issue | Pages |
1-12 | |
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| ISSN | 23673370 | ISBN | 978-981976991-9 | Medium | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 237 | ||
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| Author | Luis Chuquimarca, Boris Vintimilla & Sergio Velastin | ||||
| Title | A Review of External Quality Inspection for Fruit Grading using CNN Models | Type | Journal | ||
| Year | 2024 | Publication | Artificial Intelligence in Agriculture | Abbreviated Journal | |
| Volume | Vol. 14 | Issue | Pages |
1-20 | |
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| ISSN | 25897217 | ISBN | Medium | ||
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 254 | ||
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| Author | Juca Aulestia M., Labanda Jaramillo M., Guaman Quinche J., Coronel Romero E., Chamba Eras L., & Roberto Jacome Galarza | ||||
| Title | Open innovation at university: a systematic literature review | Type | Journal Article | ||
| Year | 2020 | Publication | Advances in Intelligent Systems and Computing | Abbreviated Journal | |
| Volume | 1159 AISC, 2020 | Issue | Pages |
3-14 | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 189 | ||
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| Author | Suárez P. | ||||
| Title | Processing and Representation of Multispectral Images Using Deep Learning Techniques | Type | Magazine Article | ||
| Year | 2021 | Publication | In Electronic Letters on Computer Vision and Image Analysis | Abbreviated Journal | |
| Volume | Vol. 19 | Issue | Issue 2 | Pages |
pp. 5-8 |
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| Corporate Author | Ph.D. Angel Sappa, Director & Ph.D. Boris Vintimilla, Codirector | Thesis | Master's thesis | ||
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| Language | Español | Summary Language | Original Title | ||
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| Notes | Approved | yes | |||
| Call Number | cidis @ cidis @ | Serial | 122 | ||
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| Author | Morocho-Cayamcela, M.E. | ||||
| Title | Increasing the Segmentation Accuracy of Aerial Images with Dilated Spatial Pyramid Pooling | Type | Journal Article | ||
| Year | 2020 | Publication | Electronic Letters on Computer Vision and Image Analysis (ELCVIA) | Abbreviated Journal | |
| Volume | Vol. 19 | Issue | Issue 2 | Pages |
pp. 17-21 |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 140 | ||
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| Author | Viñán-Ludeña M.S., De Campos L.M., Roberto Jacome Galarza, & Sinche Freire, J. | ||||
| Title | Social media influence: a comprehensive review in general and in tourism domain | Type | Journal Article | ||
| Year | 2020 | Publication | Smart Innovation, Systems and Technologies. | Abbreviated Journal | |
| Volume | 171, 2020 | Issue | Pages |
25-35 | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 190 | ||
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| Author | Angel D. Sappa; Cristhian A. Aguilera; Juan A. Carvajal Ayala; Miguel Oliveira; Dennis Romero; Boris X. Vintimilla; Ricardo Toledo | ||||
| Title | Monocular visual odometry: a cross-spectral image fusion based approach | Type | Journal Article | ||
| Year | 2016 | Publication | Robotics and Autonomous Systems Journal | Abbreviated Journal | |
| Volume | Vol. 86 | Issue | Pages |
pp. 26-36 | |
| Keywords | Monocular visual odometry LWIR-RGB cross-spectral imaging Image fusion | ||||
| Abstract | This manuscript evaluates the usage of fused cross-spectral images in a monocular visual odometry approach. Fused images are obtained through a Discrete Wavelet Transform (DWT) scheme, where the best setup is em- pirically obtained by means of a mutual information based evaluation met- ric. The objective is to have a exible scheme where fusion parameters are adapted according to the characteristics of the given images. Visual odom- etry is computed from the fused monocular images using an off the shelf approach. Experimental results using data sets obtained with two different platforms are presented. Additionally, comparison with a previous approach as well as with monocular-visible/infrared spectra are also provided showing the advantages of the proposed scheme. | ||||
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| Language | Enlgish | Summary Language | English | Original Title | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 54 | ||
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