| Records |
| Author |
Angel D. Sappa, Spencer Low, Oliver Nina, Erik Blasch, Dylan Bowald & Nathan Inkawhich |
| Title |
Multi-modal Aerial View Image Challenge: SAR Classification |
Type |
Conference Article |
| Year |
2024 |
Publication  |
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops CVPRW 2024 Seattle 16 – 22 June 2024 |
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3105 - 3112 |
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979-835036547-4 |
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Approved |
no |
| Call Number |
cidis @ cidis @ |
Serial |
234 |
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| Author |
Angel D. Sappa, Spencer Low, Oliver Nina, Erik Blasch, Dylan Bowald & Nathan Inkawhich |
| Title |
Multi-modal Aerial View Image Challenge: Sensor Domain Translation |
Type |
Conference Article |
| Year |
2024 |
Publication |
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops CVPRW 2024 Seattle 16 – 22 June 2024 |
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Pages |
3096 - 3104 |
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979-835036547-4 |
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no |
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cidis @ cidis @ |
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235 |
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| Author |
Rafael E. Rivadeneira, Angel D. Sappa and Riad Hammoud, Jiyong Rao, Hang Zhong, Yu Wang, Shengjie Zhao & et. |
| Title |
Thermal Image Super- Resolution Challenge Results – PBVS 2025 |
Type |
Conference Article |
| Year |
2025 |
Publication |
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops CVPRW 2025 |
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no |
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cidis @ cidis @ |
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274 |
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| Author |
Wassim El Ahmar, Angel D. Sappa and Riad Hammoud |
| Title |
Thermal Pedestrian MultipleObject Tracking Challenge (TPMOT) |
Type |
Conference Article |
| Year |
2025 |
Publication |
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops CVPRW 2025 |
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no |
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cidis @ cidis @ |
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275 |
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| Author |
Nathan Inkawhich, Claire Thorp, Justice Wheelwright, Oliver Nina, Dylan Bowald, Angel Sappa, Erik Blasch |
| Title |
4th Multi-modal Aerial View Image Challenge: SAR CLASSIFICATION – PBVS 2025 |
Type |
Journal Article |
| Year |
2025 |
Publication |
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops CVPRW 2025 |
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no |
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cidis @ cidis @ |
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276 |
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| Author |
Dylan Bowald, Justice Wheelwright, Oliver Nina, Angel Sappa, Riad Hammoud, Erik Blasch, Nathan Inkawhich |
| Title |
3th Multi-modal Aerial View Image Challenge: Sensor Domain Translation – PBVS 2025 |
Type |
Conference Article |
| Year |
2025 |
Publication |
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops CVPRW 2025 |
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no |
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cidis @ cidis @ |
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277 |
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| Author |
Lukas Danev; Marten Hamann; Nicolas Fricke; Tobias Hollarek; Dennys Paillacho |
| Title |
Development of animated facial expression to express emotions in a robot: RobotIcon. |
Type |
Conference Article |
| Year |
2017 |
Publication |
IEEE Ecuador Technical Chapter Meeting (ETCM) |
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2017-January |
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Pages |
1-6 |
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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 |
| Title |
Organ identification on shrimp histological images: A comparative study considering CNN and feature engineering. |
Type |
Conference Article |
| Year |
2018 |
Publication |
IEEE Ecuador Technical Chapters Meeting ETCM 2018. Cuenca, Ecuador |
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1-6 |
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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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gtsi @ user @ |
Serial |
87 |
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| Author |
Raul A. Mira; Patricia L. Suarez; Rafael E. Rivadeneira; Angel D. Sappa |
| Title |
PETRA: A Crowdsourcing-Based Platform for Rocks Data Collection and Characterization |
Type |
Conference Article |
| 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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gtsi @ user @ |
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112 |
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| Author |
Sebastián Fuenzalida; Keyla Toapanta; Jonathan S. Paillacho Corredores; Dennys Paillacho |
| Title |
Forward and Inverse Kinematics of a Humanoid Robot Head for Social Human Robot-Interaction |
Type |
Conference Article |
| Year |
2019 |
Publication |
IEEE ETCM 2019 Fourth Ecuador Technical Chapters Meeting; Guayaquil, Ecuador |
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This paper presents an analysis of forward and inverse kinematics for a humanoid robotic head. The robotic head is used for the study of social human-robot interaction, such as a support tool to maintain the attention of patients with Autism Spectrum Disorder. The design of a parallel robot that emulates human head movements through a closed structure is presented. The position and orientation in this space is controlled by three servomotors. For this, the solutions made for the kinematic problem are encompassed by a geometric analysis of a mobile base. This article describes a non-systematic method,
called the geometric method, and compares some of the most popular existing methods considering reliability and computational cost. The geometric method avoids the use of changing reference systems, and instead uses geometric
relationships to directly obtain the position based on joint variables; and the other way around. Therefore, it converges in a few iterations and has a low computational cost. |
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no |
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gtsi @ user @ |
Serial |
113 |
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