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Author (up) Armin Mehri; Angel D. Sappa pdf  openurl
  Title Colorizing Near Infrared Images through a Cyclic Adversarial Approach of Unpaired Samples Type Conference Article
  Year 2019 Publication Conference on Computer Vision and Pattern Recognition Workshops (CVPR 2019); Long Beach, California, United States Abbreviated Journal  
  Volume Issue Pages 971-979  
  Keywords  
  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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  Call Number gtsi @ user @ Serial 105  
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Author (up) Benítez-Quintero J., Quevedo-Pinos O., Calderon, Fernanda pdf  openurl
  Title Notes on Sulfur Fluxes in Urban Areas with Industrial Activity Type Conference Article
  Year 2022 Publication 20th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology, LACCEI 2022, Abbreviated Journal  
  Volume 2022-July Issue Pages  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 201  
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Author (up) Boris Vintimilla, Jorge Vulgarin, Henry Velesaca pdf  isbn
openurl 
  Title Deep Learning-based Human Height Estimation from a Stereo Vision System Type Conference Article
  Year 2023 Publication IEEE 13th International Conference on Pattern Recognition Systems (ICPRS) 2023, julio 4-7 Abbreviated Journal  
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  ISSN ISBN 979-835033337-4 Medium  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 215  
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Author (up) Byron Lima; Ricardo Cajo; Victor Huilcapi; Wilton Agila pdf  url
openurl 
  Title Modeling and comparative study of linear and nonlinear controllers for rotary inverted pendulum Type Conference Article
  Year 2017 Publication Journal of Physics: Conference Series Abbreviated Journal  
  Volume 783 Issue Pages  
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  Abstract The rotary inverted pendulum (RIP) is a problem difficult to control, several studies have been conducted where different control techniques have been applied. Literature reports that, although problem is nonlinear, classical PID controllers presents appropriate performances when applied to the system. In this paper, a comparative study of the performances of linear and nonlinear PID structures is carried out. The control algorithms are evaluated in the RIP system, using indices of performance and power consumption, which allow the categorization of control strategies according to their performance. This article also presents the modeling system, which has been estimated some of the parameters involved in the RIP system, using computer-aided design tools (CAD) and experimental methods or techniques proposed by several authors attended. The results indicate a better performance of the nonlinear controller with an increase in the robustness and faster response than the linear controller  
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  Notes Approved no  
  Call Number gtsi @ user @ Serial 69  
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Author (up) Carlos Monsalve; Alain April; Alain Abran pdf  url
openurl 
  Title BPM and requirements elicitation at multiple levels of abstraction: A review Type Conference Article
  Year 2011 Publication IADIS International Conference on Information Systems 2011 Abbreviated Journal  
  Volume Issue Pages 237-242  
  Keywords Business process modeling, levels of abstraction, requirements elicitation, requirements modeling, review  
  Abstract Business process models can be useful for requirements elicitation, among other things. Software development depends on the quality of the requirements elicitation activities, and so adequately modeling business processes (BPs) is critical. A key factor in achieving this is the active participation of all the stakeholders in the development of a shared vision of BPs.

Unfortunately, organizations often find themselves left with inconsistent BPs that do not cover all the stakeholders’ needs

and constraints. However, consolidation of the various stakeholder requirements may be facilitated through the use of multiple levels of abstraction (MLA). This article contributes to the research into MLA use in business process modeling (BPM) for software requirements by reviewing the theoretical foundations of MLA and their use in various BP-oriented approaches.
 
  Address CIDIS-FIEC, Escuela Superior Politécnica del Litoral (ESPOL) Km. 30.5 vía Perimetral,  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 15  
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Author (up) Carlos Monsalve; Alain April; Alain Abran pdf  openurl
  Title Requirements Elicitation Using BPM Notations: Focusing on the Strategic Level Representation Type Conference Article
  Year 2011 Publication 10th WSEAS international conference on Applied computer and applied computational science Abbreviated Journal  
  Volume Issue Pages 235-241  
  Keywords Business process modeling, levels of abstraction, requirements elicitation, case study, action research  
  Abstract Business process models (BPM) can be useful for requirements elicitation, among other uses. Since the active participation of all stakeholders is a key factor for successful requirements engineering, it is important that BPM be shared by all stakeholders. Unfortunately, organizations may end up with inconsistent BPM not covering all stakeholders’ needs and constraints. The use of multiple levels of abstraction (MLA), such as at the strategic, tactical and operational levels, is often used in various process-oriented initiatives to facilitate the consolidation of various stakeholders’ needs and constraints. This article surveys the use of MLA in recent BPM research publications and reports on a BPM action-research case study conducted in a Canadian organization, with the aim of exploring the usefulness of the strategic level.  
  Address CIDIS – Electrical and Computer Engineering Department Escuela Superior Politécnica del Litoral Km. 30.5 vía Perimetral  
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  Publisher Place of Publication 1100 rue Notre-Dame Ouest, Montréal, Québec H3C 1K3 CANADA Editor  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 16  
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Author (up) Cristhian A. Aguilera; Angel D. Sappa; R. Toledo pdf  url
openurl 
  Title LGHD: A feature descriptor for matching across non-linear intensity variations Type Conference Article
  Year 2015 Publication IEEE International Conference on, Quebec City, QC, 2015 Abbreviated Journal  
  Volume Issue Pages 178 - 181  
  Keywords Feature descriptor, multi-modal, multispectral, NIR, LWIR  
  Abstract This paper presents a new feature descriptor suitable to the task of matching features points between images with nonlinear intensity variations. This includes image pairs with significant illuminations changes, multi-modal image pairs and multi-spectral image pairs. The proposed method describes the neighbourhood of feature points combining frequency and spatial information using multi-scale and multi-oriented Log- Gabor filters. Experimental results show the validity of the proposed approach and also the improvements with respect to the state of the art.  
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  Publisher IEEE Place of Publication Quebec City, QC, Canada Editor  
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  Area Expedition Conference 2015 IEEE International Conference on Image Processing (ICIP)  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 40  
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Author (up) Cristhian A. Aguilera; Francisco J. Aguilera; Angel D. Sappa; Ricardo Toledo pdf  openurl
  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  
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  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.  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 48  
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Author (up) Cristhian A. Aguilera; Xaver Soria; Angel D. Sappa; Ricardo Toledo pdf  openurl
  Title RGBN Multispectral Images: a Novel Color Restoration Approach Type Conference Article
  Year 2017 Publication 15th International Conference on Practical Applications of Agents and Multi-Agent Systems Abbreviated Journal  
  Volume 619 Issue Pages 155-163  
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  Call Number cidis @ cidis @ Serial 59  
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Author (up) Cristina L. Abad; Yi Lu; Roy H. Campbell pdf  url
openurl 
  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.  
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  Notes Approved yes  
  Call Number cidis @ cidis @ Serial 21  
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