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Author Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla
Title Colorizing Infrared Images through a Triplet Condictional DCGAN Architecture Type Conference Article
Year 2017 Publication (up) 19th International Conference on Image Analysis and Processing. Abbreviated Journal
Volume Issue Pages 287-297
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Notes Approved no
Call Number gtsi @ user @ Serial 66
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Author Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla
Title Cross-spectral Image Patch Similarity using Convolutional Neural Network Type Conference Article
Year 2017 Publication (up) 2017 IEEE International Workshop of Electronics, Control, Measurement, Signals and their application to Mechatronics (ECMSM) Abbreviated Journal
Volume Issue Pages 1-5
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Notes Approved no
Call Number cidis @ cidis @ Serial 57
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Author Angel J. Valencia; Roger M. Idrovo; Angel D. Sappa; Douglas Plaza G.; Daniel Ochoa
Title A 3D Vision Based Approach for Optimal Grasp of Vacuum Grippers Type Conference Article
Year 2017 Publication (up) 2017 IEEE International Workshop of Electronics, Control, Measurement, Signals and their application to Mechatronics (ECMSM) Abbreviated Journal
Volume Issue Pages 1-6
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Notes Approved no
Call Number cidis @ cidis @ Serial 60
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Author Xavier Soria; Edgar Riba; Angel D. Sappa
Title Dense Extreme Inception Network: Towards a Robust CNN Model for Edge Detection Type Conference Article
Year 2020 Publication (up) 2020 IEEE Winter Conference on Applications of Computer Vision (WACV) Abbreviated Journal
Volume Issue 9093290 Pages 1912-1921
Keywords
Abstract This paper proposes a Deep Learning based edge de- tector, which is inspired on both HED (Holistically-Nested Edge Detection) and Xception networks. The proposed ap- proach generates thin edge-maps that are plausible for hu- man eyes; it can be used in any edge detection task without previous training or fine tuning process. As a second contri- bution, a large dataset with carefully annotated edges, has been generated. This dataset has been used for training the proposed approach as well the state-of-the-art algorithms for comparisons. Quantitative and qualitative evaluations have been performed on different benchmarks showing im- provements with the proposed method when F-measure of ODS and OIS are considered.
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ISSN ISBN 978-172816553-0 Medium
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Notes Approved no
Call Number cidis @ cidis @ Serial 126
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Author Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud
Title Near InfraRed Imagery Colorization Type Conference Article
Year 2018 Publication (up) 25 th IEEE International Conference on Image Processing, ICIP 2018 Abbreviated Journal
Volume Issue Pages 2237-2241
Keywords
Abstract This paper proposes a stacked conditional Generative

Adversarial Network-based method for Near InfraRed

(NIR) imagery colorization. We propose a variant architecture

of Generative Adversarial Network (GAN) that uses multiple

loss functions over a conditional probabilistic generative model.

We show that this new architecture/loss-function yields better

generalization and representation of the generated colored IR

images. The proposed approach is evaluated on a large test

dataset and compared to recent state of the art methods using

standard metrics.1

Index Terms—Convolutional Neural Networks (CNN), Generative

Adversarial Network (GAN), Infrared Imagery colorization.
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Notes Approved no
Call Number gtsi @ user @ Serial 81
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Author Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla
Title Learning Image Vegetation Index through a Conditional Generative Adversarial Network Type Conference Article
Year 2017 Publication (up) 2nd IEEE Ecuador Tehcnnical Chapters Meeting (ETCM) Abbreviated Journal
Volume Issue Pages
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Notes Approved no
Call Number gtsi @ user @ Serial 70
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Author Dennis G. Romero; A. Frizera; Angel D. Sappa; Boris X. Vintimilla; T.F. Bastos
Title A predictive model for human activity recognition by observing actions and context Type Conference Article
Year 2015 Publication (up) ACIVS 2015 (Advanced Concepts for Intelligent Vision Systems), International Conference on, Catania, Italy, 2015 Abbreviated Journal
Volume Issue Pages 323 - 333
Keywords Edge width, Image blu,r Defocus map, Edge model
Abstract This paper presents a novel model to estimate human activities – a human activity is defined by a set of human actions. The proposed approach is based on the usage of Recurrent Neural Networks (RNN) and Bayesian inference through the continuous monitoring of human actions and its surrounding environment. In the current work human activities are inferred considering not only visual analysis but also additional resources; external sources of information, such as context information, are incorporated to contribute to the activity estimation. The novelty of the proposed approach lies in the way the information is encoded, so that it can be later associated according to a predefined semantic structure. Hence, a pattern representing a given activity can be defined by a set of actions, plus contextual information or other kind of information that could be relevant to describe the activity. Experimental results with real data are provided showing the validity of the proposed approach.
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Notes Approved no
Call Number cidis @ cidis @ Serial 43
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Author Rafael E. Rivadeneira, Angel D. Sappa, Boris X. Vintimilla, Jin Kim, Dogun Kim et al.
Title Thermal Image Super-Resolution Challenge Results- PBVS 2022. Type Conference Article
Year 2022 Publication (up) Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. Abbreviated Journal CONFERENCE
Volume 2022-June Issue Pages 349-357
Keywords
Abstract This paper presents results from the third Thermal Image

Super-Resolution (TISR) challenge organized in the Perception Beyond the Visible Spectrum (PBVS) 2022 workshop.

The challenge uses the same thermal image dataset as the

first two challenges, with 951 training images and 50 validation images at each resolution. A set of 20 images was

kept aside for testing. The evaluation tasks were to measure

the PSNR and SSIM between the SR image and the ground

truth (HR thermal noisy image downsampled by four), and

also to measure the PSNR and SSIM between the SR image

and the semi-registered HR image (acquired with another

camera). The results outperformed those from last year’s

challenge, improving both evaluation metrics. This year,

almost 100 teams participants registered for the challenge,

showing the community’s interest in this hot topic.
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Notes Approved no
Call Number cidis @ cidis @ Serial 175
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Author P. Ricaurte; C. Chilán; C. A. Aguilera-Carrasco; B. X. Vintimilla; Angel D. Sappa
Title Performance Evaluation of Feature Point Descriptors in the Infrared Domain Type Conference Article
Year 2014 Publication (up) Computer Vision Theory and Applications (VISAPP), 2014 International Conference on, Lisbon, Portugal, 2013 Abbreviated Journal
Volume 1 Issue Pages 545 -550
Keywords Infrared Imaging, Feature Point Descriptors
Abstract This paper presents a comparative evaluation of classical feature point descriptors when they are used in the long-wave infrared spectral band. Robustness to changes in rotation, scaling, blur, and additive noise are evaluated using a state of the art framework. Statistical results using an outdoor image data set are presented together with a discussion about the differences with respect to the results obtained when images from the visible spectrum are considered.
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Publisher IEEE Place of Publication Editor
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN ISBN Medium
Area Expedition Conference 2014 International Conference on Computer Vision Theory and Applications (VISAPP)
Notes Approved no
Call Number cidis @ cidis @ Serial 26
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Author A. Amato; F. Lumbreras; Angel D. Sappa
Title A general-purpose crowdsourcing platform for mobile devices Type Conference Article
Year 2014 Publication (up) Computer Vision Theory and Applications (VISAPP), 2014 International Conference on, Lisbon, Portugal, 2014 Abbreviated Journal
Volume 3 Issue Pages 211-215
Keywords Crowdsourcing Platform, Mobile Crowdsourcing
Abstract This paper presents details of a general purpose micro-taskon-demand platform based on the crowdsourcing philosophy. This platformwas specifically developed for mobile devices in order to exploit the strengths of such devices; namely: i) massivity, ii) ubiquityand iii) embedded sensors.The combined use of mobile platforms and the crowdsourcing model allows to tackle from the simplest to the most complex tasks.Users experience is the highlighted feature of this platform (this fact is extended to both task-proposer and task- solver).Proper tools according with a specific task are provided to a task-solver in order to perform his/her job in a simpler, faster and appealing way.Moreover, a task can be easily submitted by just selecting predefined templates, which cover a wide range of possible applications.Examples of its usage in computer vision and computer games are provided illustrating the potentiality of the platform.
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Publisher IEEE Place of Publication Lisbon, Portugal 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 Computer Vision Theory and Applications (VISAPP), 2014 International Conference on
Notes Approved no
Call Number cidis @ cidis @ Serial 25
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