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Jácome Galarza, Luis Roberto |
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Title |
Estimation of Corn Crop Yield using Multimodal Deep Learning from Multispectral Images and Environmental Sensors |
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2024 |
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19ª Conferência Ibérica de Sistemas e Tecnologias de Informação; CISTI'2024 |
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cidis @ cidis @ |
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246 |
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Tommy David Beltran Borbor, Raul Josue Villao Rodriguez, Luis Enrique Chuquimarca Jiménez, Boris Xavier Vintimilla Burgos & Sergio Alejandro Velastin |
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Title |
Fruit Deformity Classification through Single-Input and Multi-Input Architectures based on CNN Models using Real and Synthetic Images |
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Conference Article |
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2024 |
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Accepted in 27th The Iberomican Congress on Pattern Recognition CIARP 2024 |
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cidis @ cidis @ |
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251 |
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Dennys Paillacho Chiluiza & Steven Silva Mendoza |
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Title |
Exploring the Perceptions and Challenges of Social Robot Navigation: Two Case Studies in Different Socio-Technical Contexts |
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2024 |
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Accepted in 36th Australian Conference on Human-Computer Interaction |
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cidis @ cidis @ |
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252 |
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Patricia Suarez Riofrio & Angel D. Sappa |
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Title |
Thermal Image Synthesis: Bridging the Gap between Visible and Infrared Spectrum |
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2024 |
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Accepted in 19th International Symposium on Visual Computing 2024 |
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no |
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cidis @ cidis @ |
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253 |
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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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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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English |
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English |
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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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Author |
A. Amato; F. Lumbreras; Angel D. Sappa |
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Title |
A general-purpose crowdsourcing platform for mobile devices |
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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, 2014 |
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3 |
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211-215 |
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Crowdsourcing Platform, Mobile Crowdsourcing |
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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 |
Place of Publication |
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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English |
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English |
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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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Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2024) Rome 27 – 29 February 2024 |
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Vol. 3: VISAPP |
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765-771 |
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no |
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Call Number |
cidis @ cidis @ |
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240 |
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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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2016 |
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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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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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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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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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gtsi @ user @ |
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120 |
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