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Author Velesaca, Henry O.; Suárez, Patricia L.; Sappa, Angel D.; Carpio, Dario; Rivadeneira, Rafael E.; Sanchez, Angel url  openurl
  Title Review on Common Techniques for Urban Environment Video Analytics. Type Conference Article
  Year 2022 Publication WORKSHOP BRASILEIRO DE CIDADES INTELIGENTES (WBCI 2022) Abbreviated Journal  
  Volume Issue Porto Alegre: Sociedade Brasileira de Computação Pages 107-118  
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  Area Expedition Conference  
  Notes Approved yes  
  Call Number cidis @ cidis @ Serial 192  
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Author Pereira J., Mora M. & W. Agila url  openurl
  Title Qualitative Model to Maximize Shrimp Growth at Low Cost Type Journal Article
  Year 2021 Publication 5th Ecuador Technical Chapters Meeting (ETCM 2021), Octubre 12 – 15 Abbreviated Journal  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 167  
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Author Jorge L. Charco, Angel D. Sappa, Boris X. Vintimilla pdf  openurl
  Title Human Pose Estimation through A Novel Multi-View Scheme Type Conference Article
  Year 2022 Publication 17th International Conference on Computer Vision Theory and Applications (VISAPP 2022), febrero 6-8 Abbreviated Journal  
  Volume 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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  Notes Approved yes  
  Call Number cidis @ cidis @ Serial 169  
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Author Xavier Soria , Gonzalo Pomboza-Junez & Angel Sappa. url  openurl
  Title LDC: Lightweight Dense CNN for Edge Detection. Type Journal Article
  Year 2022 Publication IEEE Access journal Abbreviated Journal  
  Volume Vol. 10 Issue Pages pp. 68281-68290  
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  Notes Approved yes  
  Call Number cidis @ cidis @ Serial 183  
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Author Rivadeneira, Rafael E.; Sappa, Angel D. and Vintimilla Boris X. url  openurl
  Title Thermal Image Super-Resolution: A Novel Unsupervised Approach. Type Book Chapter
  Year 2022 Publication Communications in Computer and Information Science, 15th International Communications in Computer and Information Science Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications Abbreviated Journal BOOK  
  Volume 1474 Issue Pages 495-506  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 179  
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Author Rafael E. Rivadeneira, Angel D. Sappa, Boris X. Vintimilla, Jin Kim, Dogun Kim et al. pdf  url
openurl 
  Title Thermal Image Super-Resolution Challenge Results- PBVS 2022. Type Conference Article
  Year 2022 Publication Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. Abbreviated Journal CONFERENCE  
  Volume 2022-June Issue Pages 349-357  
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  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 Rangnekar,Aneesha; Mulhollan,Zachary; Vodacek,Anthony; Hoffman,Matthew; Sappa,Angel D.; Yu,Jun et al. pdf  openurl
  Title Semi-Supervised Hyperspectral Object Detection Challenge Results-PBVS 2022. Type Conference Article
  Year 2022 Publication Conference on Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. Abbreviated Journal CONFERENCE  
  Volume 2022-June Issue Pages 389-397  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 176  
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Author Low S., Inkawhich N., Nina O., Sappa A. and Blasch E. pdf  url
openurl 
  Title Multi-modal Aerial View Object Classification Challenge Results-PBVS 2022. Type Conference Article
  Year 2022 Publication Conference on Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. Abbreviated Journal CONFERENCE  
  Volume 2022-June Issue Pages 417-425  
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  Abstract This paper details the results and main findings of the

second iteration of the Multi-modal Aerial View Object

Classification (MAVOC) challenge. This year’s MAVOC

challenge is the second iteration. The primary goal of

both MAVOC challenges is to inspire research into methods for building recognition models that utilize both synthetic aperture radar (SAR) and electro-optical (EO) input

modalities. Teams are encouraged/challenged to develop

multi-modal approaches that incorporate complementary

information from both domains. While the 2021 challenge

showed a proof of concept that both modalities could be

used together, the 2022 challenge focuses on the detailed

multi-modal models. Using the same UNIfied COincident

Optical and Radar for recognitioN (UNICORN) dataset and

competition format that was used in 2021. Specifically, the

challenge focuses on two techniques, (1) SAR classification

and (2) SAR + EO classification. The bulk of this document is dedicated to discussing the top performing methods

and describing their performance on our blind test set. Notably, all of the top ten teams outperform our baseline. For

SAR classification, the top team showed a 129% improvement over our baseline and an 8% average improvement

from the 2021 winner. The top team for SAR + EO classification shows a 165% improvement with a 32% average

improvement over 2021.
 
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 177  
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Author Velez R., Paredes A., Silva S., Paillacho D., and Paillacho J. url  openurl
  Title Implementation of a UVC lights disinfection system for a diferential robot applying security methods in indoor. Type Conference Article
  Year 2022 Publication Communications in Computer and Information Science, International Conference on Applied Technologies (ICAT 2021), octubre 27-29 Abbreviated Journal CONFERENCE  
  Volume 1535 Issue Pages 319-331  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 178  
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Author Nayeth I. Solorzano, L. C. H., Leslie del R. Lima, Dennys F. Paillacho & Jonathan S. Paillacho url  openurl
  Title Visual Metrics for Educational Videogames Linked to Socially Assistive Robots in an Inclusive Education Framework Type Conference Article
  Year 2022 Publication Smart Innovation, Systems and Technologies. International Conference in Information Technology & Education (ICITED 21), julio 15-17 Abbreviated Journal  
  Volume 256 Issue Pages 119-132  
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  Abstract In gamification, the development of “visual metrics for educational

video games linked to social assistance robots in the framework of inclusive education” seeks to provide support, not only to regular children but also to children with specific psychosocial disabilities, such as those diagnosed with autism spectrum disorder (ASD). However, personalizing each child's experiences represents a limitation, especially for those with atypical behaviors. 'LOLY,' a social assistance robot, works together with mobile applications associated with the family of educational video game series called 'MIDI-AM,' forming a social robotic platform. This platform offers the user curricular digital content to reinforce the teaching-learning processes and motivate regular children and those with ASD. In the present study, technical, programmatic experiments and focus groups were carried out, using open-source facial recognition algorithms to monitor and evaluate the degree of user attention throughout the interaction. The objective is to evaluate the management of a social robot linked to educational video games

through established metrics, which allow monitoring the user's facial expressions

during its use and define a scenario that ensures consistency in the results for its applicability in therapies and reinforcement in the teaching process, mainly

adaptable for inclusive early childhood education.
 
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  Area Expedition Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 180  
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