|
Records |
Links |
|
Author |
Rivadeneira R.E., Sappa A.D., Vintimilla B.X., Nathan S., Kansal P., Mehri A et al. |
|
|
Title |
Thermal Image Super-Resolution Challenge – PBVS 2021. |
Type |
Conference Article |
|
Year |
2021 |
Publication |
In IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021., junio 19 – 25, 2021 |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
4354-4362 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
|
Approved |
no |
|
|
Call Number |
cidis @ cidis @ |
Serial |
151 |
|
Permanent link to this record |
|
|
|
|
Author |
Mehri, A, Ardakani, P.B., Sappa, A.D. |
|
|
Title |
MPRNet: Multi-Path Residual Network for Lightweight Image Super Resolution. |
Type |
Conference Article |
|
Year |
2021 |
Publication |
In IEEE Winter Conference on Applications of Computer Vision WACV 2021, enero 5-9, 2021 |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
2703-2712 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
|
Approved |
no |
|
|
Call Number |
cidis @ cidis @ |
Serial |
148 |
|
Permanent link to this record |
|
|
|
|
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 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
Ph.D. Angel Sappa, Director & Ph.D. Boris Vintimilla, Codirector |
Thesis |
Master's thesis |
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
Español |
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
|
Approved |
yes |
|
|
Call Number |
cidis @ cidis @ |
Serial |
122 |
|
Permanent link to this record |
|
|
|
|
Author |
Velesaca, H.O., Suárez, P. L., Mira, R., & Sappa, A.D. |
|
|
Title |
Computer Vision based Food Grain Classification: a Comprehensive Survey |
Type |
Journal Article |
|
Year |
2021 |
Publication |
In Computers and Electronics in Agriculture Journal. (Article number 106287) |
Abbreviated Journal |
|
|
|
Volume |
Vol. 187 |
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
|
Approved |
no |
|
|
Call Number |
cidis @ cidis @ |
Serial |
159 |
|
Permanent link to this record |
|
|
|
|
Author |
Steven Silva, Nervo Verdezoto, Dennys Paillacho, Samuel Millan-Norman & Juan David Hernandez |
|
|
Title |
Online Social Robot Navigation in Indoor, Large and Crowded Environments. |
Type |
Conference Article |
|
Year |
2023 |
Publication |
IEEE International Conference on Robotics and Automation (ICRA 2023) |
Abbreviated Journal |
|
|
|
Volume |
2023-May |
Issue |
|
Pages |
9749 - 9756 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
10504729 |
ISBN |
979-835032365-8 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
|
Approved |
no |
|
|
Call Number |
cidis @ cidis @ |
Serial |
206 |
|
Permanent link to this record |
|
|
|
|
Author |
Patricia L. Suárez, Angel D. Sappa, Boris X. Vintimilla |
|
|
Title |
Cycle generative adversarial network: towards a low-cost vegetation index estimation |
Type |
Conference Article |
|
Year |
2021 |
Publication |
IEEE International Conference on Image Processing (ICIP 2021) |
Abbreviated Journal |
|
|
|
Volume |
2021-September |
Issue |
|
Pages |
2783-2787 |
|
|
Keywords |
CyclicGAN, NDVI, near infrared spectra, instance normalization. |
|
|
Abstract |
This paper presents a novel unsupervised approach to estimate the Normalized Difference Vegetation Index (NDVI).The NDVI is obtained as the ratio between information from the visible and near infrared spectral bands; in the current work, the NDVI is estimated just from an image of the visible spectrum through a Cyclic Generative Adversarial Network (CyclicGAN). This unsupervised architecture learns to estimate the NDVI index by means of an image translation between the red channel of a given RGB image and the NDVI unpaired index’s image. The translation is obtained by means of a ResNET architecture and a multiple loss function. Experimental results obtained with this unsupervised scheme show the validity of the implemented model. Additionally, comparisons with the state of the art approaches are provided showing improvements with the proposed approach. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
|
Approved |
no |
|
|
Call Number |
cidis @ cidis @ |
Serial |
164 |
|
Permanent link to this record |
|
|
|
|
Author |
Cristhian A. Aguilera; Francisco J. Aguilera; Angel D. Sappa; Ricardo Toledo |
|
|
Title |
Learning crossspectral similarity measures with deep convolutional neural networks |
Type |
Conference Article |
|
Year |
2016 |
Publication |
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) Workshops |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
267-275 |
|
|
Keywords |
|
|
|
Abstract |
The simultaneous use of images from different spectra can be helpful to improve the performance of many com- puter vision tasks. The core idea behind the usage of cross- spectral approaches is to take advantage of the strengths of each spectral band providing a richer representation of a scene, which cannot be obtained with just images from one spectral band. In this work we tackle the cross-spectral image similarity problem by using Convolutional Neural Networks (CNNs). We explore three different CNN archi- tectures to compare the similarity of cross-spectral image patches. Specifically, we train each network with images from the visible and the near-infrared spectrum, and then test the result with two public cross-spectral datasets. Ex- perimental results show that CNN approaches outperform the current state-of-art on both cross-spectral datasets. Ad- ditionally, our experiments show that some CNN architec- tures are capable of generalizing between different cross- spectral domains. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
English |
Summary Language |
English |
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
|
Approved |
no |
|
|
Call Number |
cidis @ cidis @ |
Serial |
48 |
|
Permanent link to this record |
|
|
|
|
Author |
Cristina L. Abad; Yi Lu; Roy H. Campbell |
|
|
Title |
DARE: Adaptive Data Replication for Efficient Cluster Scheduling |
Type |
Conference Article |
|
Year |
2011 |
Publication |
IEEE International Conference on Cluster Computing, 2011 |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
159 - 168 |
|
|
Keywords |
MapReduce, replication, scheduling, locality |
|
|
Abstract |
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. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
English |
Summary Language |
English |
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
|
Approved |
yes |
|
|
Call Number |
cidis @ cidis @ |
Serial |
21 |
|
Permanent link to this record |
|
|
|
|
Author |
Silva Steven, Paillacho Dennys, Verdezoto Nervo, Hernandez Juan David |
|
|
Title |
TOWARDS ONLINE SOCIALLY ACCEPTABLE ROBOT NAVIGATION |
Type |
Conference Article |
|
Year |
2022 |
Publication |
IEEE INTERNATIONAL CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING, |
Abbreviated Journal |
|
|
|
Volume |
2022-August |
Issue |
|
Pages |
707-714 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
|
Approved |
no |
|
|
Call Number |
cidis @ cidis @ |
Serial |
199 |
|
Permanent link to this record |
|
|
|
|
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 |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
1-6 |
|
|
Keywords |
|
|
|
Abstract |
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. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
|
Approved |
no |
|
|
Call Number |
gtsi @ user @ |
Serial |
112 |
|
Permanent link to this record |