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Luis Chuquimarca, Boris Vintimilla & Sergio Velastin |
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Banana Ripeness Level Classification using a Simple CNN Model Trained with Real and Synthetic Datasets. |
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2023 |
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Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISIGRAPP 2023 |
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536 - 543 |
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cidis @ cidis @ |
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202 |
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Author |
Julien Poujol; Cristhian A. Aguilera; Etienne Danos; Boris X. Vintimilla; Ricardo Toledo; Angel D. Sappa |
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Title |
A visible-Thermal Fusion based Monocular Visual Odometry |
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2015 |
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Iberian Robotics Conference (ROBOT 2015), International Conference on, Lisbon, Portugal, 2015 |
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417 |
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517-528 |
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Monocular Visual Odometry; LWIR-RGB cross-spectral Imaging; Image Fusion |
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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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English |
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cidis @ cidis @ |
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44 |
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Spencer Low, Oliver Nina, Angel D. Sappa, Erik Blasch, Nathan Inkawhich |
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Multi-modal Aerial View Image Challenge: Translation from Synthetic Aperture Radar to Electro-Optical Domain Results – PBVS 2023 |
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Conference Article |
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2023 |
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19th IEEE Workshop on Perception Beyond the Visible Spectrum de la Conferencia Computer Vision & Pattern Recognition CVPR 2023, junio 18-28 |
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2023-June |
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515 - 523 |
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21607508 |
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979-835030249-3 |
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cidis @ cidis @ |
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211 |
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Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla |
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Title |
Image patch similarity through a meta-learning metric based approach |
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2019 |
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15th International Conference on Signal Image Technology & Internet based Systems (SITIS 2019); Sorrento, Italia |
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511-517 |
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Comparing images regions are one of the core methods used on computer vision for tasks like image classification, scene understanding, object detection and recognition. Hence, this paper proposes a novel approach to determine similarity of image regions (patches), in order to obtain the best representation of image patches. This problem has been studied by many researchers presenting different approaches, however, the ability to find the better criteria to measure the similarity on image regions are still a challenge. The present work tackles this problem using a few-shot metric based meta-learning framework able to compare image regions and determining a similarity measure to decide if there is similarity between the compared patches. Our model is training end-to-end from scratch. Experimental results
have shown that the proposed approach effectively estimates the similarity of the patches and, comparing it with the state of the art approaches, shows better results. |
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gtsi @ user @ |
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115 |
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