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Author  |
Ángel Morera, Ángel Sánchez, A. Belén Moreno, Angel D. Sappa, & José F. Vélez |
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Title |
SSD vs. YOLO for Detection of Outdoor Urban Advertising Panels under Multiple Variabilities. |
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Journal Article |
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Year |
2020 |
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Abbreviated Journal |
In Sensors |
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Volume |
Vol. 2020-August |
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16 |
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pp. 1-23 |
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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 |
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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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14248220 |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
133 |
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Author |
Angely Oyola; Dennis G. Romero; Boris X. Vintimilla |
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Title |
A Dijkstra-based algorithm for selecting the Shortest-Safe Evacuation Routes in dynamic environments (SSER) |
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Conference Article |
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2017 |
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The 30th International Conference on Industrial, Engineering, Other Applications of Applied Intelligent Systems (IEA/AIE 2017) |
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131-135 |
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no |
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Call Number |
cidis @ cidis @ |
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55 |
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Author |
Arias Alexandra. Ing.; Peña Roxanna. Ing.; Chávez Patricia. MSEE.; Basurto Juan. Ing |
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Title |
Análisis Comparativo de la Implementación de una PBX de Código Abierto instalada en un Servidor Tradicional y en un Enrutador Inalámbrico en términos de Calidad de Servicio en Redes Inalámbricas Amalladas |
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Journal Article |
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2011 |
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Revista Tecnologica ESPOL RTE |
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Vol. 24 |
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pp. 1-6 |
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Keywords |
Redes Inalámbricas Mesh, VoIP, Asterisk |
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Abstract |
El presente trabajo compara dos Implementaciones de Centrales Telefónicas VoIP de Código Abierto implementados sobre una Red Inalámbrica Amallada. El primero comprende la instalación de la PBX en un servidor tradicional y el segundo la instalación de una PBX en un enrutador inalámbrico. Nuestro objetivo es
determinar cuál de estos dos sistemas es superior en cuanto a calidad de servicio se refiere. Para determinar la mejor solución, realizamos un estudio técnico de los paquetes capturados durante diferentes pruebas, considerando parámetros como el ancho de banda, retardo y jitter. Nuestros métodos de análisis pueden ser utilizados para futuros trabajos con una mayor complejidad y número de enrutadores inalámbrico, así como establecer el grado de afectación y el comportamiento de las dos PBX cuando haya congestión en la red. |
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Escuela Superior Politécnica del Litoral Km 30.5 vía Perimetral |
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Guayaquil, Guayas Ecuador |
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Español |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
14 |
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Author |
Armin Mehri, Parichehr Behjati, Dario Carpio, and Angel D. Sappa |
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Title |
SRFormer: Efficient Yet Powerful Transformer Network For Single Image Super Resolution |
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Journal Article |
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Year |
2023 |
Publication |
IEEE access |
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Vol. 11 |
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Pages |
121457 - 121469 |
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21693536 |
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no |
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Call Number |
cidis @ cidis @ |
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227 |
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Author |
Armin Mehri; Angel D. Sappa |
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Title |
Colorizing Near Infrared Images through a Cyclic Adversarial Approach of Unpaired Samples |
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Conference Article |
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Year |
2019 |
Publication |
Conference on Computer Vision and Pattern Recognition Workshops (CVPR 2019); Long Beach, California, United States |
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971-979 |
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Abstract |
This paper presents a novel approach for colorizing
near infrared (NIR) images. The approach is based on
image-to-image translation using a Cycle-Consistent adversarial network for learning the color channels on unpaired dataset. This architecture is able to handle unpaired datasets. The approach uses as generators tailored
networks that require less computation times, converge
faster and generate high quality samples. The obtained results have been quantitatively—using standard evaluation
metrics—and qualitatively evaluated showing considerable
improvements with respect to the state of the art |
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gtsi @ user @ |
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105 |
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Author |
Armin Mehri; Parichehr Behjati; Angel Domingo Sappa |
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Title |
TnTViT-G: Transformer in Transformer Network for Guidance Super Resolution. |
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Journal Article |
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Year |
2023 |
Publication |
IEEE Access |
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Volume |
Vol. 11 |
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Pages |
pp. 11529-11540 |
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21693536 |
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Call Number |
cidis @ cidis @ |
Serial |
207 |
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Author |
Benítez-Quintero J., Quevedo-Pinos O., Calderon, Fernanda |
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Title |
Notes on Sulfur Fluxes in Urban Areas with Industrial Activity |
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Conference Article |
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Year |
2022 |
Publication |
20th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology, LACCEI 2022, |
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2022-July |
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Call Number |
cidis @ cidis @ |
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201 |
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Author |
Boris Vintimilla, Jorge Vulgarin, Henry Velesaca |
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Title |
Deep Learning-based Human Height Estimation from a Stereo Vision System |
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Conference Article |
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Year |
2023 |
Publication |
IEEE 13th International Conference on Pattern Recognition Systems (ICPRS) 2023, julio 4-7 |
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979-835033337-4 |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
215 |
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Author |
Carlos Monsalve; Alain April and Alain Abran |
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Title |
Measuring software functional size from business process models |
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Journal Article |
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Year |
2011 |
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International Journal of Software Engineering and Knowledge Engineering |
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Vol. 21 |
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pp. 311–338 |
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Abstract |
ISO 14143-1 specifies that a functional size measurement (FSM) method must provide measurement procedures to quantify the functional user requirements (FURs) of software. Such quantitative information, functional size, is typically used, for instance, in software estimation. One of the international standards for FSM is the COSMIC FSM method — ISO 19761 — which was designed to be applied both to the business application (BA) software domain and to the real-time software domain. A recurrent problem in FSM is the availability and quality of the inputs required for measurement purposes; that is, well documented FURs. Business process (BP) models, as they are commonly used to gather requirements from the early stages of a project, could be a valuable source of information for FSM. In a previous article, the feasibility of such an approach for the BA domain was analyzed using the Qualigram BP modeling notation. This paper complements that work by: (1) analyzing the use of BPMN for FSM in the BA domain; (2) presenting notation-independent guidelines for the BA domain; and (3) analyzing the possibility of using BP models to perform FSM in the real-time domain. The measurement results obtained from BP models are compared with those of previous FSM case studies. |
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English |
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English |
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Call Number |
cidis @ cidis @ |
Serial |
19 |
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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 |
Publication |
In Image and Vision Computing Journal. (Article number 104182) |
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Vol. 110 |
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Keywords |
Relative camera pose estimation, Domain adaptation, Siamese architecture, Synthetic data, Multi-view environments |
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Abstract |
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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English |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
147 |
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