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Author |
Luis Chuquimarca, Boris Vintimilla & Sergio Velastin |
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Title |
Banana Ripeness Level Classification using a Simple CNN Model Trained with Real and Synthetic Datasets. |
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Conference Article |
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Year |
2023 |
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Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) Lisbon, 19-21 Febrero 2023 |
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Vol. 5 |
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536 - 543 |
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21845921 |
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no |
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Call Number |
cidis @ cidis @ |
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202 |
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Author |
Miguel Realpe; Boris X. Vintimilla; Ljubo Vlacic |
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Title |
Multi-sensor Fusion Module in a Fault Tolerant Perception System for Autonomous Vehicles |
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Journal Article |
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Year |
2016 |
Publication |
Journal of Automation and Control Engineering (JOACE) |
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Vol. 4 |
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pp. 430-436 |
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Keywords |
Fault Tolerance, Data Fusion, Multi-sensor Fusion, Autonomous Vehicles, Perception System |
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Driverless vehicles are currently being tested on public roads in order to examine their ability to perform in a safe and reliable way in real world situations. However, the long-term reliable operation of a vehicle’s diverse sensors and the effects of potential sensor faults in the vehicle system have not been tested yet. This paper is proposing a sensor fusion architecture that minimizes the influence of a sensor fault. Experimental results are presented simulating faults by introducing displacements in the sensor information from the KITTI dataset. |
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English |
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no |
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cidis @ cidis @ |
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51 |
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Author |
Jorge L. Charco; Angel D. Sappa; Boris X. Vintimilla; Henry O. Velesaca |
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Title |
Transfer Learning from Synthetic Data in the Camera Pose Estimation Problem |
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Conference Article |
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Year |
2020 |
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The 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020); Valletta, Malta; 27-29 Febrero 2020 |
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4 |
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498-505 |
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Keywords |
Relative Camera Pose Estimation, Siamese Architecture, Synthetic Data, Deep Learning, Multi-View Environments, Extrinsic Camera Parameters. |
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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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978-989758402-2 |
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no |
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Call Number |
gtsi @ user @ |
Serial |
120 |
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Author |
Rafael E. Rivadeneira; Angel D. Sappa; Boris X. Vintimilla |
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Title |
Thermal Image Super-Resolution: a Novel Architecture and Dataset |
Type |
Conference Article |
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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 |
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4 |
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111-119 |
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Keywords |
Thermal images, Far Infrared, Dataset, Super-Resolution. |
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This paper proposes a novel CycleGAN architecture for thermal image super-resolution, together with a large
dataset consisting of thermal images at different resolutions. The dataset has been acquired using three thermal
cameras at different resolutions, which acquire images from the same scenario at the same time. The thermal
cameras are mounted in rig trying to minimize the baseline distance to make easier the registration problem.
The proposed architecture is based on ResNet6 as a Generator and PatchGAN as Discriminator. The novelty
on the proposed unsupervised super-resolution training (CycleGAN) is possible due to the existence of aforementioned thermal images—images of the same scenario with different resolutions. The proposed approach
is evaluated in the dataset and compared with classical bicubic interpolation. The dataset and the network are
available. |
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978-989758402-2 |
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no |
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gtsi @ user @ |
Serial |
121 |
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Author |
Rafael E. Rivadeneira, Angel D. Sappa and Boris X. Vintimilla |
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Title |
Multi-Image Super-Resolution for Thermal Images. |
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Conference Article |
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Year |
2022 |
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Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISIGRAPP 2022 |
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4 |
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Pages |
635 - 642 |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
181 |
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Author |
Luis Chuquimarca, Renzo Pacheco, Paula Gonzalez, Boris Vintimilla & Sergio Velastin |
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Title |
Fruit defect detection using CNN models with real and virtual data. |
Type |
Conference Article |
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Year |
2023 |
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18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) Lisbon 19-21 Febraury 2024 |
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Vol. 4 |
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272 - 279 |
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21845921 |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
203 |
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Author |
A. Amato; F. Lumbreras; Angel D. Sappa |
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Title |
A general-purpose crowdsourcing platform for mobile devices |
Type |
Conference Article |
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Year |
2014 |
Publication |
Computer Vision Theory and Applications (VISAPP), 2014 International Conference on, Lisbon, Portugal, 2014 |
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3 |
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211-215 |
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Keywords |
Crowdsourcing Platform, Mobile Crowdsourcing |
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Abstract |
This paper presents details of a general purpose micro-taskon-demand platform based on the crowdsourcing philosophy. This platformwas specifically developed for mobile devices in order to exploit the strengths of such devices; namely: i) massivity, ii) ubiquityand iii) embedded sensors.The combined use of mobile platforms and the crowdsourcing model allows to tackle from the simplest to the most complex tasks.Users experience is the highlighted feature of this platform (this fact is extended to both task-proposer and task- solver).Proper tools according with a specific task are provided to a task-solver in order to perform his/her job in a simpler, faster and appealing way.Moreover, a task can be easily submitted by just selecting predefined templates, which cover a wide range of possible applications.Examples of its usage in computer vision and computer games are provided illustrating the potentiality of the platform. |
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IEEE |
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Lisbon, Portugal |
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English |
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English |
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Computer Vision Theory and Applications (VISAPP), 2014 International Conference on |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
25 |
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Author |
N. Onkarappa; Cristhian A. Aguilera; B. X. Vintimilla; Angel D. Sappa |
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Title |
Cross-spectral Stereo Correspondence using Dense Flow Fields |
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Conference Article |
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Year |
2014 |
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Computer Vision Theory and Applications (VISAPP), 2014 International Conference on, Lisbon, Portugal, 2014 |
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3 |
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613 - 617 |
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Cross-spectral Stereo Correspondence, Dense Optical Flow, Infrared and Visible Spectrum |
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This manuscript addresses the cross-spectral stereo correspondence problem. It proposes the usage of a dense flow field based representation instead of the original cross-spectral images, which have a low correlation. In this way, working in the flow field space, classical cost functions can be used as similarity measures. Preliminary experimental results on urban environments have been obtained showing the validity of the proposed approach. |
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IEEE |
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2014 International Conference on Computer Vision Theory and Applications (VISAPP) |
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no |
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Call Number |
cidis @ cidis @ |
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27 |
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Author |
Patricia Suarez, Angel D. Sappa |
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Title |
A Generative Model for Guided Thermal Image Super-Resolution |
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Conference Article |
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2024 |
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19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2024 Rome 27 – 29 Febraury 2024 |
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Vol. 3: VISAPP |
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765-771 |
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cidis @ cidis @ |
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240 |
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Author |
P. Ricaurte; C. Chilán; C. A. Aguilera-Carrasco; B. X. Vintimilla; Angel D. Sappa |
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Title |
Performance Evaluation of Feature Point Descriptors in the Infrared Domain |
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Conference Article |
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2014 |
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Computer Vision Theory and Applications (VISAPP), 2014 International Conference on, Lisbon, Portugal, 2013 |
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1 |
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545 -550 |
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Keywords |
Infrared Imaging, Feature Point Descriptors |
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This paper presents a comparative evaluation of classical feature point descriptors when they are used in the long-wave infrared spectral band. Robustness to changes in rotation, scaling, blur, and additive noise are evaluated using a state of the art framework. Statistical results using an outdoor image data set are presented together with a discussion about the differences with respect to the results obtained when images from the visible spectrum are considered. |
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IEEE |
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2014 International Conference on Computer Vision Theory and Applications (VISAPP) |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
26 |
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