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Author (up) Henry Velesaca Lara, Juan Antonio Holgado & José Miguel Gutiérrez openurl 
  Title Optimizing Smart Factory Operations: A Methodological Approach to Industrial System Implementation based on OPC-UA Type Conference Article
  Year 2024 Publication Accepted in CIIA – II International Conference of Applied Industrial Engineering Abbreviated Journal  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 242  
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Author (up) Henry Velesaca Lara, Patricia Suarez, Darío Carpio & Angel Sappa openurl 
  Title Fruit Grading based on Deep Learning and Active Vision System Type Conference Article
  Year 2024 Publication Accepted in CIIA – II International Conference of Applied Industrial Engineering Abbreviated Journal  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 241  
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Author (up) Henry Velesaca, Boris Vintimilla, Jorge Vulgarin, Coen Antens & Alberto Rubio Pérez openurl 
  Title Deep Learning-based Multimodal Sensing Framework for AntiSpoofing Systems Type Journal Article
  Year 2024 Publication In Fourth International Conference on Innovations in Computational Intelligence and Computer Vision (ICICV 2024) Abbreviated Journal  
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  Call Number cidis @ cidis @ Serial 238  
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Author (up) 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 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 (up) Jorge L. Charco, Angel D. Sappa, Boris X. Vintimilla, Henry O. Velesaca. url  openurl
  Title 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 (up) Juca Aulestia M., Labanda Jaramillo M., Guaman Quinche J., Coronel Romero E., Chamba Eras L., & Roberto Jacome Galarza url  openurl
  Title Open innovation at university: a systematic literature review Type Journal Article
  Year 2020 Publication Advances in Intelligent Systems and Computing Abbreviated Journal  
  Volume 1159 AISC, 2020 Issue Pages 3-14  
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  Call Number cidis @ cidis @ Serial 189  
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Author (up) 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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  Call Number cidis @ cidis @ Serial 177  
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Author (up) Luis C. Herrera, Leslie del R. Lima, Nayeth I. Solorzano, Jonathan S. Paillacho & Dennys Paillacho. url  openurl
  Title Metrics Design of Usability and Behavior Analysis of a Human-Robot-Game Platform. Type Conference Article
  Year 2021 Publication The 2nd International Conference on Applied Technologies (ICAT 2020), diciembre 2-4. Communication in Computer and Information Science Abbreviated Journal  
  Volume 1388 Issue Pages 164-178  
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  Call Number cidis @ cidis @ Serial 191  
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Author (up) Luis Chuquimarca, Boris Vintimilla & Sergio Velastin pdf  openurl
  Title Banana Ripeness Level Classification using a Simple CNN Model Trained with Real and Synthetic Datasets. 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 536 - 543  
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  Call Number cidis @ cidis @ Serial 202  
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Author (up) Luis Chuquimarca, Boris X. Vintimilla & Sergio Velastin openurl 
  Title Classifying Healthy and Defective Fruits with a Siamese Architecture and CNN Models Type Conference Article
  Year 2024 Publication Accepted in 14th International Conference on Pattern Recognition Systems (ICPRS) Abbreviated Journal  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 245  
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