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Author | Luis Chuquimarca, Renzo Pacheco, Paula Gonzalez, Boris Vintimilla & Sergio Velastin | ||||
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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Author | Luis Chuquimarca, Boris X. Vintimilla & Sergio Velastin | ||||
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 | Luis Chuquimarca, Boris Vintimilla & Sergio Velastin | ||||
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 | Luis C. Herrera, Leslie del R. Lima, Nayeth I. Solorzano, Jonathan S. Paillacho & Dennys Paillacho. | ||||
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 | Low S., Inkawhich N., Nina O., Sappa A. and Blasch E. | ||||
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 | Juan A. Carvajal; Dennis G. Romero; Angel D. Sappa | ||||
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 | José Reyes; Axel Godoy; Miguel Realpe. | ||||
Title | Uso de software de código abierto para fusión de imágenes agrícolas multiespectrales adquiridas con drones. | Type | Conference Article | ||
Year | 2019 | Publication | International Multi-Conference of Engineering, Education and Technology (LACCEI 2019); Montego Bay, Jamaica | Abbreviated Journal | |
Volume | 2019-July | Issue | Pages | ||
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Abstract | Los drones o aeronaves no tripuladas son muy útiles para la adquisición de imágenes, de forma mucho más simple que los satélites o aviones. Sin embargo, las imágenes adquiridas por drones deben ser combinadas de alguna forma para convertirse en información de valor sobre un terreno o cultivo. Existen diferentes programas que reciben imágenes y las combinan en una sola imagen, cada uno con diferentes características (rendimiento, precisión, resultados, precio, etc.). En este estudio se revisaron diferentes programas de código abierto para fusión de imágenes, con el ?n de establecer cuál de ellos es más útil, especí?camente para ser utilizado por pequeños y medianos agricultores en Ecuador. Los resultados pueden ser de interés para diseñadores de software, ya que al utilizar código abierto, es posible modi?car e integrar los programas en un ?ujo de trabajo más simpli?cado. Además, que permite disminuir costos debido a que no requiere de pagos de licencias para su uso, lo cual puede repercutir en un mayor acceso a la tecnología para los pequeños y medianos agricultores. Como parte de los resultados de este estudio se ha creado un repositorio de acceso público con algoritmos de pre-procesamiento necesarios para manipular las imágenes adquiridas por una cámara multiespectral y para luego obtener un mapa completo en formatos RGB, CIR y NDVI. | ||||
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Call Number | gtsi @ user @ | Serial | 102 | ||
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Author | Jorge L. Charco; Boris X. Vintimilla; Angel D. Sappa | ||||
Title | Deep learning based camera pose estimation in multi-view environment. | Type | Conference Article | ||
Year | 2018 | Publication | 14th IEEE International Conference on Signal Image Technology & Internet based Systems (SITIS 2018) | Abbreviated Journal | |
Volume | Issue | Pages | 224-228 | ||
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Abstract | This paper proposes to use a deep learning network architecture for relative camera pose estimation on a multi-view environment. The proposed network is a variant architecture of AlexNet to use as regressor for prediction the relative translation and rotation as output. The proposed approach is trained from scratch on a large data set that takes as input a pair of images from the same scene. This new architecture is compared with a previous approach using standard metrics, obtaining better results on the relative camera pose. | ||||
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Call Number | gtsi @ user @ | Serial | 93 | ||
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Author | Jorge L. Charco; Angel D. Sappa; Boris X. Vintimilla; Henry O. Velesaca | ||||
Title | Transfer Learning from Synthetic Data in the Camera Pose Estimation Problem | Type | Conference Article | ||
Year | 2020 | Publication | The 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020); Valletta, Malta; 27-29 Febrero 2020 | Abbreviated Journal | |
Volume | 4 | Issue | Pages | 498-505 | |
Keywords | Relative Camera Pose Estimation, Siamese Architecture, Synthetic Data, Deep Learning, Multi-View Environments, Extrinsic Camera Parameters. | ||||
Abstract | This paper presents a novel Siamese network architecture, as a variant of Resnet-50, to estimate the relative camera pose on multi-view environments. In order to improve the performance of the proposed model a transfer learning strategy, based on synthetic images obtained from a virtual-world, is considered. The transfer learning consist of first training the network using pairs of images from the virtual-world scenario considering different conditions (i.e., weather, illumination, objects, buildings, etc.); then, the learned weight of the network are transferred to the real case, where images from real-world scenarios are considered. Experimental results and comparisons with the state of the art show both, improvements on the relative pose estimation accuracy using the proposed model, as well as further improvements when the transfer learning strategy (synthetic-world data – transfer learning – real-world data) is considered to tackle the limitation on the training due to the reduced number of pairs of real-images on most of the public data sets. |
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ISSN | ISBN | 978-989758402-2 | Medium | ||
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Call Number | gtsi @ user @ | Serial | 120 | ||
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Author | Jorge L. Charco, Angel D. Sappa, Boris X. Vintimilla, Henry O. Velesaca. | ||||
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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