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Author |
Gisel Bastidas-Guacho, Patricio Moreno-Vallejo, Boris Vintimilla, Angel D. Sappa |
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Title |
Application on the Loop of Multimodal Image Fusion: Trends on Deep-Learning Based Approaches |
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Conference Article |
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Year |
2023 |
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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 |
213 |
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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 |
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IEEE Access |
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Vol. 11 |
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pp. 11529-11540 |
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21693536 |
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no |
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cidis @ cidis @ |
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207 |
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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 |
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IEEE access |
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Vol. 11 |
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121457 - 121469 |
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21693536 |
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no |
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cidis @ cidis @ |
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227 |
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Author |
Xavier Soria , Gonzalo Pomboza-Junez & Angel Sappa. |
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Title |
LDC: Lightweight Dense CNN for Edge Detection. |
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Journal Article |
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2022 |
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IEEE Access journal |
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Vol. 10 |
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pp. 68281-68290 |
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yes |
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cidis @ cidis @ |
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183 |
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Author |
Lukas Danev; Marten Hamann; Nicolas Fricke; Tobias Hollarek; Dennys Paillacho |
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Title |
Development of animated facial expression to express emotions in a robot: RobotIcon. |
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Conference Article |
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Year |
2017 |
Publication |
IEEE Ecuador Technical Chapter Meeting (ETCM) |
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2017-January |
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1-6 |
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no |
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gtsi @ user @ |
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71 |
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Author |
Milton Mendieta; F. Panchana; B. Andrade; B. Bayot; C. Vaca; Boris X. Vintimilla; Dennis G. Romero |
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Title |
Organ identification on shrimp histological images: A comparative study considering CNN and feature engineering. |
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Conference Article |
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Year |
2018 |
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IEEE Ecuador Technical Chapters Meeting ETCM 2018. Cuenca, Ecuador |
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1-6 |
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Abstract |
The identification of shrimp organs in biology using
histological images is a complex task. Shrimp histological images
poses a big challenge due to their texture and similarity among
classes. Image classification by using feature engineering and
convolutional neural networks (CNN) are suitable methods to
assist biologists when performing organ detection. This work
evaluates the Bag-of-Visual-Words (BOVW) and Pyramid-Bagof-
Words (PBOW) models for image classification leveraging big
data techniques; and transfer learning for the same classification
task by using a pre-trained CNN. A comparative analysis
of these two different techniques is performed, highlighting
the characteristics of both approaches on the shrimp organs
identification problem. |
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no |
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Call Number |
gtsi @ user @ |
Serial |
87 |
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Author |
Raul A. Mira; Patricia L. Suarez; Rafael E. Rivadeneira; Angel D. Sappa |
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Title |
PETRA: A Crowdsourcing-Based Platform for Rocks Data Collection and Characterization |
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Conference Article |
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Year |
2019 |
Publication |
IEEE ETCM 2019 Fourth Ecuador Technical Chapters Meeting; Guayaquil, Ecuador |
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1-6 |
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This paper presents details of a distributed platform intended for data acquisition, evaluation, storage and visualization, which is fully implemented under the crowdsourcing paradigm. The proposed platform is the result from collaboration between computer science and petrology researchers and it is intended for academic purposes. The platform is designed within a MTV (Model, Template and View) architecture and also designed for a collaborative data store and managing of rocks from multiple readers and writers, taking advantage of ubiquity of web applications, and neutrality of researchers from different
communities to validate the data. The platform is being used and validated by students and academics from our university; in the near future it will be open to other users interested on this topic. |
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no |
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Call Number |
gtsi @ user @ |
Serial |
112 |
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Author |
W. Agila; Gomer Rubio; L. Miranda; D. Sanaguano |
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Title |
Open Control Architecture for the Characterization and Control of the PEM Fuel Cell |
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Conference Article |
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Year |
2019 |
Publication |
IEEE ETCM 2019 Fourth Ecuador Technical Chapters Meeting; Guayaquil, Ecuador |
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1-5 |
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PEM fuel cell, Experimental System, Control Engineering. |
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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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gtsi @ user @ |
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118 |
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Author |
Silva Steven, Paillacho Dennys, Verdezoto Nervo, Hernandez Juan David |
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Title |
TOWARDS ONLINE SOCIALLY ACCEPTABLE ROBOT NAVIGATION |
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Conference Article |
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2022 |
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IEEE INTERNATIONAL CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING, |
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2022-August |
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707-714 |
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cidis @ cidis @ |
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199 |
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Author |
Cristina L. Abad; Yi Lu; Roy H. Campbell |
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Title |
DARE: Adaptive Data Replication for Efficient Cluster Scheduling |
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2011 |
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IEEE International Conference on Cluster Computing, 2011 |
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159 - 168 |
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MapReduce, replication, scheduling, locality |
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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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English |
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English |
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yes |
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cidis @ cidis @ |
Serial |
21 |
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