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| Author | Miguel Oliveira; Vítor Santos; Angel D. Sappa; Paulo Dias; A. Paulo Moreira | ||||
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Incremental Texture Mapping for Autonomous Driving | Type | Journal Article | ||
| Year | 2016 | Publication | Robotics and Autonomous Systems Journal | Abbreviated Journal | |
| Volume | Vol. 84 | Issue | Pages | pp. 113-128 | |
| Keywords | Scene reconstruction, Autonomous driving, Texture mapping | ||||
| Abstract | Autonomous vehicles have a large number of on-board sensors, not only for providing coverage all around the vehicle, but also to ensure multi-modality in the observation of the scene. Because of this, it is not trivial to come up with a single, unique representation that feeds from the data given by all these sensors. We propose an algorithm which is capable of mapping texture collected from vision based sensors onto a geometric description of the scenario constructed from data provided by 3D sensors. The algorithm uses a constrained Delaunay triangulation to produce a mesh which is updated using a specially devised sequence of operations. These enforce a partial configuration of the mesh that avoids bad quality textures and ensures that there are no gaps in the texture. Results show that this algorithm is capable of producing fine quality textures. | ||||
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| Language | English | Summary Language | English | Original Title | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 50 | ||
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| Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla | ||||
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Infrared Image Colorization based on a Triplet DCGAN Architecture. | Type | Conference Article | ||
| Year | 2017 | Publication | 13th IEEE Workshop on Perception Beyond the Visible Spectrum – In conjunction with CVPR 2017. (This paper has been selected as “Best Paper Award” ) | Abbreviated Journal | |
| Volume | 2017-July | Issue | Pages | 212-217 | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 62 | ||
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| Author | Jorge Alvarez Tello; Mireya Zapata; Dennys Paillacho | ||||
| Title |
Kinematic optimization of a robot head movements for the evaluation of human-robot interaction in social robotics. | Type | Conference Article | ||
| Year | 2019 | Publication | 10th International Conference on Applied Human Factors and Ergonomics and the Affiliated Conferences (AHFE 2019), Washington D.C.; United States. Advances in Intelligent Systems and Computing | Abbreviated Journal | |
| Volume | 975 | Issue | Pages | 108-118 | |
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| Abstract | This paper presents the simplification of the head movements from the analysis of the biomechanical parameters of the head and neck at the mechanical and structural level through CAD modeling and construction with additive printing in ABS/PLA to implement non-verbal communication strategies and establish behavior patterns in the social interaction. This is using in the denominated MASHI (Multipurpose Assistant robot for Social Human-robot Interaction) experimental robotic telepresence platform, implemented by a display with a fish-eye camera along with the mechanical mechanism, which permits 4 degrees of freedom (DoF). In the development of mathematicalmechanical modeling for the kinematics codification that governs the robot and the autonomy of movement, we have the Pitch, Roll, and Yaw movements, and the combination of all of them to establish an active communication through telepresence. For the computational implementation, it will be show the rotational matrix to describe the movement. |
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| Notes | Approved | yes | |||
| Call Number | gtsi @ user @ | Serial | 108 | ||
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| Author | Morocho-Cayamcela, M.E. & W. Lim | ||||
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Lateral confinement of high-impedance surface-waves through reinforcement learning | Type | Journal Article | ||
| Year | 2020 | Publication | Electronics Letters | Abbreviated Journal | |
| Volume | Vol. 56 | Issue | 23, 12 November 2020 | Pages | pp. 1262-1264 |
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| Abstract | The authors present a model-free policy-based reinforcement learning model that introduces perturbations on the pattern of a metasurface. The objective is to learn a policy that changes the size of the patches, and therefore the impedance in the sides of an artificially structured material. The proposed iterative model assigns the highest reward when the patch sizes allow the transmission along a constrained path and penalties when the patch sizes make the surface wave radiate to the sides of the metamaterial. After convergence, the proposed model learns an optimal patch pattern that achieves lateral confinement along the metasurface. Simulation results show that the proposed learned-pattern can effectively guide the electromagnetic wave through a metasurface, maintaining its instantaneous eigenstate when the homogeneity is perturbed. Moreover, the pattern learned to prevent reflections by changing the patch sizes adiabatically. The reflection coefficient S1, 2 shows that most of the power gets transferred from the source to the destination with the proposed design. |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 139 | ||
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| Author | Xavier Soria , Gonzalo Pomboza-Junez & Angel Sappa. | ||||
| Title |
LDC: Lightweight Dense CNN for Edge Detection. | Type | Journal Article | ||
| Year | 2022 | Publication | IEEE Access journal | Abbreviated Journal | |
| Volume | Vol. 10 | Issue | Pages | pp. 68281-68290 | |
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| Call Number | cidis @ cidis @ | Serial | 183 | ||
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| Author | Cristhian A. Aguilera; Francisco J. Aguilera; Angel D. Sappa; Ricardo Toledo | ||||
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Learning crossspectral similarity measures with deep convolutional neural networks | Type | Conference Article | ||
| Year | 2016 | Publication | IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) Workshops | Abbreviated Journal | |
| Volume | Issue | Pages | 267-275 | ||
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| Abstract | The simultaneous use of images from different spectra can be helpful to improve the performance of many com- puter vision tasks. The core idea behind the usage of cross- spectral approaches is to take advantage of the strengths of each spectral band providing a richer representation of a scene, which cannot be obtained with just images from one spectral band. In this work we tackle the cross-spectral image similarity problem by using Convolutional Neural Networks (CNNs). We explore three different CNN archi- tectures to compare the similarity of cross-spectral image patches. Specifically, we train each network with images from the visible and the near-infrared spectrum, and then test the result with two public cross-spectral datasets. Ex- perimental results show that CNN approaches outperform the current state-of-art on both cross-spectral datasets. Ad- ditionally, our experiments show that some CNN architec- tures are capable of generalizing between different cross- spectral domains. | ||||
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 48 | ||
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| Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla | ||||
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Learning Image Vegetation Index through a Conditional Generative Adversarial Network | Type | Conference Article | ||
| Year | 2017 | Publication | 2nd IEEE Ecuador Tehcnnical Chapters Meeting (ETCM) | Abbreviated Journal | |
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| Notes | Approved | no | |||
| Call Number | gtsi @ user @ | Serial | 70 | ||
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| Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla | ||||
| Title |
Learning to Colorize Infrared Images | Type | Conference Article | ||
| Year | 2017 | Publication | 15th International Conference on Practical Applications of Agents and Multi-Agent Systems | Abbreviated Journal | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 58 | ||
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| Author | Cristhian A. Aguilera; Angel D. Sappa; R. Toledo | ||||
| Title |
LGHD: A feature descriptor for matching across non-linear intensity variations | Type | Conference Article | ||
| Year | 2015 | Publication | IEEE International Conference on, Quebec City, QC, 2015 | Abbreviated Journal | |
| Volume | Issue | Pages | 178 - 181 | ||
| Keywords | Feature descriptor, multi-modal, multispectral, NIR, LWIR | ||||
| Abstract | This paper presents a new feature descriptor suitable to the task of matching features points between images with nonlinear intensity variations. This includes image pairs with significant illuminations changes, multi-modal image pairs and multi-spectral image pairs. The proposed method describes the neighbourhood of feature points combining frequency and spatial information using multi-scale and multi-oriented Log- Gabor filters. Experimental results show the validity of the proposed approach and also the improvements with respect to the state of the art. | ||||
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| Publisher | IEEE | Place of Publication | Quebec City, QC, Canada | Editor | |
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| Area | Expedition | Conference | 2015 IEEE International Conference on Image Processing (ICIP) | ||
| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 40 | ||
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| Author | Mehri, A, Ardakani, P.B., Sappa, A.D. | ||||
| Title |
LiNet: A Lightweight Network for Image Super Resolution | Type | Conference Article | ||
| Year | 2021 | Publication | 25th International Conference on Pattern Recognition (ICPR), enero 10-15, 2021 | Abbreviated Journal | |
| Volume | Issue | Pages | 7196-7202 | ||
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| Call Number | cidis @ cidis @ | Serial | 149 | ||
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