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Author (up) Juan A. Carvajal; Dennis G. Romero; Angel D. Sappa pdf  openurl
  Title 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 (up) Juan A. Carvajal; Dennis G. Romero; Angel D. Sappa pdf  openurl
  Title 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  
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  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 (up) Juan C. Basurto, Patricia Chávez and Hernán Córdova pdf  openurl
  Title A Proximity-Aware Transparent Handoff Mobility Scheme for VoIP Communication over Infrastructure Mesh Networks Type Conference Article
  Year 2011 Publication International Congress of Electronic, Electrical and Systems Engineering-INTERCON 2011 Abbreviated Journal  
  Volume Issue Pages  
  Keywords Wireless Mesh Networks; Quality of Service; Mobility Management; Voice over IP.  
  Abstract Mobility Management plays a key role in Voice-over- IP (VoIP) communications over Wireless Mesh Networks (WMN) as clients should maintain adequate levels of Quality of Service (QoS) as they move across the network. This paper presents PATH, a Proximity-Aware Transparent Handoff mobility scheme for real time voice communications over wireless mesh networks. Our study focuses on Medium Access Control (MAC) layer procedures and relies on gratuitous ARP unicasting in order to provide fast-handoffs. An experimental evaluation has been conducted and its results are shown in this paper.  
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  Call Number cidis @ cidis @ Serial 20  
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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) Julien Poujol; Cristhian A. Aguilera; Etienne Danos; Boris X. Vintimilla; Ricardo Toledo; Angel D. Sappa pdf  url
openurl 
  Title A visible-Thermal Fusion based Monocular Visual Odometry Type Conference Article
  Year 2015 Publication Iberian Robotics Conference (ROBOT 2015), International Conference on, Lisbon, Portugal, 2015 Abbreviated Journal  
  Volume 417 Issue Pages 517-528  
  Keywords Monocular Visual Odometry; LWIR-RGB cross-spectral Imaging; Image Fusion  
  Abstract The manuscript evaluates the performance of a monocular visual odometry approach when images from different spectra are considered, both independently and fused. The objective behind this evaluation is to analyze if classical approaches can be improved when the given images, which are from different spectra, are fused and represented in new domains. The images in these new domains should have some of the following properties: i) more robust to noisy data; ii) less sensitive to changes (e.g., lighting); iii) more rich in descriptive information, among other. In particular in the current work two different image fusion strategies are considered. Firstly, images from the visible and thermal spectrum are fused using a Discrete Wavelet Transform (DWT) approach. Secondly, a monochrome threshold strategy is considered. The obtained representations are evaluated under a visual odometry framework, highlighting their advantages and disadvantages, using different urban and semi-urban scenarios. Comparisons with both monocular-visible spectrum and monocular-infrared spectrum, are also provided showing the validity of the proposed approach.  
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  Call Number cidis @ cidis @ Serial 44  
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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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  Call Number cidis @ cidis @ Serial 245  
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Author (up) Luis Chuquimarca, Renzo Pacheco, Paula Gonzalez, Boris Vintimilla & Sergio Velastin pdf  openurl
  Title 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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