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Author Mónica Villavicencio; Alain Abran
Title (up) Facts and Perceptions Regarding Software Measurement in Education and in Practice: Preliminary Results Type Journal Article
Year 2011 Publication Journal of Software Engineering and Application Abbreviated Journal
Volume Issue Pages pp. 227-234
Keywords Software measurement, education, software engineering
Abstract How is software measurement addressed in undergraduate and graduate programs in universities? Do organizations consider that the graduating students they hire have an adequate knowledge of software measurement? To answer these and related questions, a survey was administered to participants who attended the IWSM-MENSURA 2010 conference in Stuttgart, Germany. Forty-seven of the 69 conference participants (including software development practitioners, software measurement consultants, university professors, and graduate students) took part in the survey. The results indicate that software measurement topics are: A) covered mostly at the graduate level and not at the undergraduate level, and B) not mandatory. Graduate students and professors consider that, of the measurement topics covered in university curricula, specific topics, such as measures for the requirements phase, and measurement techniques and tools, receive more attention in the academic context. A common observation of the practitioners who participated in the survey was that students hired as new employees bring limited software measurement-related knowledge to their organizations. Discussion of the findings and directions for future research are presented.
Address 2 CIDIS-FIEC, Escuela Superior Politécnica del Litoral (ESPOL), Guayaquil, Ecuador
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Call Number cidis @ cidis @ Serial 17
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Author Cristhian A. Aguilera, Cristhian Aguilera, Cristóbal A. Navarro, & Angel D. Sappa
Title (up) Fast CNN Stereo Depth Estimation through Embedded GPU Devices Type Journal Article
Year 2020 Publication Sensors 2020 Abbreviated Journal
Volume Vol. 2020-June Issue 11 Pages pp. 1-13
Keywords stereo matching; deep learning; embedded GPU
Abstract Current CNN-based stereo depth estimation models can barely run under real-time

constraints on embedded graphic processing unit (GPU) devices. Moreover, state-of-the-art

evaluations usually do not consider model optimization techniques, being that it is unknown what is

the current potential on embedded GPU devices. In this work, we evaluate two state-of-the-art models

on three different embedded GPU devices, with and without optimization methods, presenting

performance results that illustrate the actual capabilities of embedded GPU devices for stereo depth

estimation. More importantly, based on our evaluation, we propose the use of a U-Net like architecture

for postprocessing the cost-volume, instead of a typical sequence of 3D convolutions, drastically

augmenting the runtime speed of current models. In our experiments, we achieve real-time inference

speed, in the range of 5–32 ms, for 1216  368 input stereo images on the Jetson TX2, Jetson Xavier,

and Jetson Nano embedded devices.
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Language English Summary Language English Original Title
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Series Volume Series Issue Edition
ISSN 14248220 ISBN Medium
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Notes Approved no
Call Number cidis @ cidis @ Serial 132
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Author Ricaurte P; Chilán C; Cristhian A. Aguilera; Boris X. Vintimilla; Angel D. Sappa
Title (up) Feature Point Descriptors: Infrared and Visible Spectra Type Journal Article
Year 2014 Publication Sensors Journal Abbreviated Journal
Volume Vol. 14 Issue Pages pp. 3690-3701
Keywords cross-spectral imaging; feature point descriptors
Abstract This manuscript evaluates the behavior of classical feature point descriptors when they are used in images from long-wave infrared spectral band and compare them with the results obtained in the visible spectrum. Robustness to changes in rotation, scaling, blur, and additive noise are analyzed using a state of the art framework. Experimental results using a cross-spectral outdoor image data set are presented and conclusions from these experiments are given.
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Call Number cidis @ cidis @ Serial 28
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Author Juan A. Carvajal; Dennis G. Romero; Angel D. Sappa
Title (up) Fine-tuning based deep covolutional networks for lepidopterous genus recognition Type Conference Article
Year 2016 Publication XXI IberoAmerican Congress on Pattern Recognition Abbreviated Journal
Volume Issue Pages 1-9
Keywords
Abstract This paper describes an image classi cation approach ori- ented to identify specimens of lepidopterous insects recognized at Ecuado- rian ecological reserves. This work seeks to contribute to studies in the area of biology about genus of butter ies and also to facilitate the reg- istration of unrecognized specimens. The proposed approach is based on the ne-tuning of three widely used pre-trained Convolutional Neural Networks (CNNs). This strategy is intended to overcome the reduced number of labeled images. Experimental results with a dataset labeled by expert biologists, is presented|a recognition accuracy above 92% is reached. 1 Introductio
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Call Number cidis @ cidis @ Serial 53
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Author Juan A. Carvajal; Dennis G. Romero; Angel D. Sappa
Title (up) Fine-tuning deep convolutional networks for lepidopterous genus recognition Type Journal Article
Year 2017 Publication Lecture Notes in Computer Science Abbreviated Journal
Volume Vol. 10125 LNCS Issue Pages pp. 467-475
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Call Number gtsi @ user @ Serial 63
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Author Sebastián Fuenzalida; Keyla Toapanta; Jonathan S. Paillacho Corredores; Dennys Paillacho
Title (up) 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 Abbreviated Journal
Volume Issue Pages
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Abstract 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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Call Number gtsi @ user @ Serial 113
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Author Luis Chuquimarca, Renzo Pacheco, Paula Gonzalez, Boris Vintimilla & Sergio Velastin
Title (up) Fruit defect detection using CNN models with real and virtual data. Type Conference Article
Year 2023 Publication Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISIGRAPP 2023 Abbreviated Journal
Volume Issue Pages 272 - 279
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Call Number cidis @ cidis @ Serial 203
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Author Jorge L. Charco, Angel D. Sappa, Boris X. Vintimilla, Henry O. Velesaca.
Title (up) Human Body Pose Estimation in Multi-view Environments. Type Book Chapter
Year 2022 Publication ICT Applications for Smart Cities Part of the Intelligent Systems Reference Library book series Abbreviated Journal BOOK
Volume 224 Issue Pages 79-99
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Call Number cidis @ cidis @ Serial 197
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Author Jorge L. Charco, Angel D. Sappa, Boris X. Vintimilla
Title (up) Human Pose Estimation through A Novel Multi-View Scheme Type Conference Article
Year 2022 Publication Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISIGRAPP 2022 Abbreviated Journal
Volume 5 Issue Pages 855-862
Keywords Multi-View Scheme, Human Pose Estimation, Relative Camera Pose, Monocular Approach
Abstract This paper presents a multi-view scheme to tackle the challenging problem of the self-occlusion in human

pose estimation problem. The proposed approach first obtains the human body joints of a set of images,

which are captured from different views at the same time. Then, it enhances the obtained joints by using a

multi-view scheme. Basically, the joints from a given view are used to enhance poorly estimated joints from

another view, especially intended to tackle the self occlusions cases. A network architecture initially proposed

for the monocular case is adapted to be used in the proposed multi-view scheme. Experimental results and

comparisons with the state-of-the-art approaches on Human3.6m dataset are presented showing improvements

in the accuracy of body joints estimations.
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Call Number cidis @ cidis @ Serial 169
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Author Angel D. Sappa.
Title (up) ICT Applications for Smart Cities Type Book Chapter
Year 2022 Publication Intelligent Systems Reference Library Abbreviated Journal BOOK
Volume 224 Issue Pages
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Call Number cidis @ cidis @ Serial 198
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