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| Author | Rafael E. Rivadeneira; Angel D. Sappa; Boris X. Vintimilla; Lin Guo; Jiankun Hou; Armin Mehri; Parichehr Behjati; Ardakani Heena Patel; Vishal Chudasama; Kalpesh Prajapati; Kishor P. Upla; Raghavendra Ramachandra; Kiran Raja; Christoph Busch; Feras Almasri; Olivier Debeir; Sabari Nathan; Priya Kansal; Nolan Gutierrez; Bardia Mojra; William J. Beksi | ||||
| Title | Thermal Image Super-Resolution Challenge – PBVS 2020 | Type | Conference Article | ||
| Year | 2020 | Publication | The 16th IEEE Workshop on Perception Beyond the Visible Spectrum on the Conference on Computer Vision and Pattern Recongnition (CVPR 2020) | Abbreviated Journal | |
| Volume | 2020-June | Issue | 9151059 | Pages | 432-439 |
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| Abstract | This paper summarizes the top contributions to the first challenge on thermal image super-resolution (TISR) which was organized as part of the Perception Beyond the Visible Spectrum (PBVS) 2020 workshop. In this challenge, a novel thermal image dataset is considered together with stateof-the-art approaches evaluated under a common framework. The dataset used in the challenge consists of 1021 thermal images, obtained from three distinct thermal cameras at different resolutions (low-resolution, mid-resolution, and high-resolution), resulting in a total of 3063 thermal images. From each resolution, 951 images are used for training and 50 for testing while the 20 remaining images are used for two proposed evaluations. The first evaluation consists of downsampling the low-resolution, midresolution, and high-resolution thermal images by x2, x3 and x4 respectively, and comparing their super-resolution results with the corresponding ground truth images. The second evaluation is comprised of obtaining the x2 superresolution from a given mid-resolution thermal image and comparing it with the corresponding semi-registered highresolution thermal image. Out of 51 registered participants, 6 teams reached the final validation phase. |
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| Language | English | Summary Language  |
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| ISSN | 21607508 | ISBN | 978-172819360-1 | Medium | |
| Area | Expedition | Conference | |||
| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 123 | ||
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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 | 2020 IEEE Winter Conference on Applications of Computer Vision (WACV) | Abbreviated Journal | |
| Volume | Issue | 9093290 | Pages | 1912-1921 | |
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| 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 | Henry O. Velesaca; Raul A. Mira; Patricia L. Suarez; Christian X. Larrea; Angel D. Sappa. | ||||
| Title | Deep Learning based Corn Kernel Classification. | Type | Conference Article | ||
| Year | 2020 | Publication | The 1st International Workshop and Prize Challenge on Agriculture-Vision: Challenges & Opportunities for Computer Vision in Agriculture on the Conference Computer on Vision and Pattern Recongnition (CVPR 2020) | Abbreviated Journal | |
| Volume | 2020-June | Issue | 9150684 | Pages | 294-302 |
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| Abstract | This paper presents a full pipeline to classify sample sets of corn kernels. The proposed approach follows a segmentation-classification scheme. The image segmentation is performed through a well known deep learning based approach, the Mask R-CNN architecture, while the classification is performed by means of a novel-lightweight network specially designed for this task—good corn kernel, defective corn kernel and impurity categories are considered. As a second contribution, a carefully annotated multitouching corn kernel dataset has been generated. This dataset has been used for training the segmentation and the classification modules. Quantitative evaluations have been performed and comparisons with other approaches provided showing improvements with the proposed pipeline. |
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| ISSN | 21607508 | ISBN | 978-172819360-1 | Medium | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 124 | ||
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| Author | Henry O. Velesaca, Steven Araujo, Patricia L. Suarez, Ángel Sanchez & Angel D. Sappa | ||||
| Title | Off-the-Shelf Based System for Urban Environment Video Analytics. | Type | Conference Article | ||
| Year | 2020 | Publication | The 27th International Conference on Systems, Signals and Image Processing (IWSSIP 2020) | Abbreviated Journal | |
| Volume | 2020-July | Issue | 9145121 | Pages | 459-464 |
| Keywords | Greenhouse gases, carbon footprint, object detection, object tracking, website framework, off-the-shelf video analytics. | ||||
| Abstract | This paper presents the design and implementation details of a system build-up by using off-the-shelf algorithms for urban video analytics. The system allows the connection to public video surveillance camera networks to obtain the necessary information to generate statistics from urban scenarios (e.g., amount of vehicles, type of cars, direction, numbers of persons, etc.). The obtained information could be used not only for traffic management but also to estimate the carbon footprint of urban scenarios. As a case study, a university campus is selected to evaluate the performance of the proposed system. The system is implemented in a modular way so that it is being used as a testbed to evaluate different algorithms. Implementation results are provided showing the validity and utility of the proposed approach. |
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| ISSN | 21578672 | ISBN | 978-172817539-3 | Medium | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 125 | ||
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| Author | Nayeth I. Solorzano Alcivar, Robert Loor, Stalyn Gonzabay Yagual, & Boris X. Vintimilla | ||||
| Title | Statistical Representations of a Dashboard to Monitor Educational Videogames in Natural Language | Type | Conference Article | ||
| Year | 2020 | Publication | ETLTC – ACM Chapter: International Conference on Educational Technology, Language and Technical Communication; Fukushima, Japan, 27-31 Enero 2020 | Abbreviated Journal | |
| Volume | 77 | Issue | Pages | ||
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| Abstract | This paper explains how Natural Language (NL) processing by computers, through smart programs as a way of Machine Learning (ML), can represent large sets of quantitative data as written statements. The study recognized the need to improve the implemented web platform using a dashboard in which we collected a set of extensive data to measure assessment factors of using children´s educational games. In this case, applying NL is a strategy to give assessments, build, and display more precise written statements to enhance the understanding of children´s gaming behavior. We propose the development of a new tool to assess the use of written explanations rather than a statistical representation of feedback information for the comprehension of parents and teachers with a lack of primary level knowledge in statistics. Applying fuzzy logic theory, we present verbatim explanations of children´s behavior playing educational videogames as NL interpretation instead of statistical representations. An educational series of digital game applications for mobile devices, identified as MIDI (Spanish acronym of “Interactive Didactic Multimedia for Children”) linked to a dashboard in the cloud, is evaluated using the dashboard metrics. MIDI games tested in local primary schools helps to evaluate the results of using the proposed tool. The guiding results allow analyzing the degrees of playability and usability factors obtained from the data produced when children play a MIDI game. The results obtained are presented in a comprehensive guiding evaluation report applying NL for parents and teachers. These guiding evaluations are useful to enhance children's learning understanding related to the school curricula applied to ludic digital games. |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 131 | ||
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| Author | Dennys Paillacho; Nayeth I. Solorzano Alcivar; Jonathan S. Paillacho Corredores | ||||
| Title | LOLY 1.0: A Proposed Human-Robot-Game Platform Architecture for the Engagement of Children with Autism in the Learning Process | Type | Book Chapter | ||
| Year | 2021 | Publication | The international Conference on Systems and Information Sciences (ICCIS 2020), julio 27-29. Advances in Intelligent Systems and Computing. | Abbreviated Journal | |
| Volume | 1273 | Issue | Pages | 225-238 | |
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| ISSN | 21945357 | ISBN | 978-303059193-9 | Medium | |
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| Notes | Approved | yes | |||
| Call Number | cidis @ cidis @ | Serial | 185 | ||
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| Author | Morocho-Cayamcela, M.E. & W. Lim | ||||
| Title | Lateral confinement of high-impedance surface-waves through reinforcement learning | Type | Journal Article | ||
| Year | 2020 | Publication | Electronics Letters | Abbreviated Journal | |
| Volume | Vol. 56 | Issue | 23, 12 November 2020 | Pages | pp. 1262-1264 |
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| Abstract | The authors present a model-free policy-based reinforcement learning model that introduces perturbations on the pattern of a metasurface. The objective is to learn a policy that changes the size of the patches, and therefore the impedance in the sides of an artificially structured material. The proposed iterative model assigns the highest reward when the patch sizes allow the transmission along a constrained path and penalties when the patch sizes make the surface wave radiate to the sides of the metamaterial. After convergence, the proposed model learns an optimal patch pattern that achieves lateral confinement along the metasurface. Simulation results show that the proposed learned-pattern can effectively guide the electromagnetic wave through a metasurface, maintaining its instantaneous eigenstate when the homogeneity is perturbed. Moreover, the pattern learned to prevent reflections by changing the patch sizes adiabatically. The reflection coefficient S1, 2 shows that most of the power gets transferred from the source to the destination with the proposed design. |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 139 | ||
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| Author | Miguel A. Murillo, Julio E. Alvia, & Miguel Realpe | ||||
| Title | Beyond visual and radio line of sight UAVs monitoring system through open software in a simulated environment. | Type | Conference Article | ||
| Year | 2021 | Publication | The 2nd International Conference on Applied Technologies (ICAT 2020), diciembre 2-4. Communications in Computer and Information Science | Abbreviated Journal | |
| Volume | 1388 | Issue | Pages | 629-642 | |
| Keywords | Drone, Open Source, Internet, Web Application, Web Server, SITL, Line of sight, UAV. | ||||
| Abstract | The problem of loss of line of sight when operating drones has be-come a reality with adverse effects for professional and amateur drone opera-tors, since it brings technical problems such as loss of data collected by the de-vice in one or more instants of time during the flight and even misunderstand-ings of legal nature when the drone flies over prohibited or private places. This paper describes the implementation of a drone monitoring system using the In-ternet as a long-range communication network in order to avoid the problem of loss of communication between the ground station and the device. For this, a simulated environment is used through an appropriate open software tool. The operation of the system is based on a client that makes requests to a server, the latter in turn communicates with several servers, each of which has a drone connected to it. In the proposed system when a drone is ready to start a flight, its server informs the main server of the system, which in turn gives feedback to the client informing it that the device is ready to carry out the flight; this way customers can send a mission to the device and keep track of its progress in real time on the screen of their web application. | ||||
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| Call Number | cidis @ cidis @ | Serial | 186 | ||
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| Author | Patricia L. Suárez, Angel D. Sappa and Boris X. Vintimilla | ||||
| Title | Deep learning-based vegetation index estimation | Type | Book Chapter | ||
| Year | 2021 | Publication | Generative Adversarial Networks for Image-to-Image Translation Book. | Abbreviated Journal | |
| Volume | Chapter 9 | Issue | Issue 2 | Pages | 205-232 |
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| Call Number | cidis @ cidis @ | Serial | 137 | ||
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| Author | Morocho-Cayamcela, M.E. | ||||
| Title | Increasing the Segmentation Accuracy of Aerial Images with Dilated Spatial Pyramid Pooling | Type | Journal Article | ||
| Year | 2020 | Publication | Electronic Letters on Computer Vision and Image Analysis (ELCVIA) | Abbreviated Journal | |
| Volume | Vol. 19 | Issue | Issue 2 | Pages | pp. 17-21 |
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| Call Number | cidis @ cidis @ | Serial | 140 | ||
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