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| Author | Michael Teutsch, Angel Sappa & Riad Hammoud | ||||
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Computer Vision in the Infrared Spectrum: Challenges and ApproachesComputer Vision in the Infrared Spectrum: Challenges and Approaches | Type | Journal Article | ||
| Year | 2021 | Publication | Synthesis Lectures on Computer Vision | Abbreviated Journal | |
| Volume | Vol. 10 No. 2 | Issue | Pages | pp. 138 | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 166 | ||
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| Author | M. Oliveira; L. Seabra Lopes; G. Hyun Lim; S. Hamidreza Kasaei; Angel D. Sappa; A. Tomé | ||||
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Concurrent Learning of Visual Codebooks and Object Categories in Open- ended Domains | Type | Conference Article | ||
| Year | 2015 | Publication | Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International Conference on, Hamburg, Germany, 2015 | Abbreviated Journal | |
| Volume | Issue | Pages | 2488 - 2495 | ||
| Keywords | Birds, Training, Legged locomotion, Visualization, Histograms, Object recognition, Gaussian mixture model | ||||
| Abstract | In open-ended domains, robots must continuously learn new object categories. When the training sets are created offline, it is not possible to ensure their representativeness with respect to the object categories and features the system will find when operating online. In the Bag of Words model, visual codebooks are usually constructed from training sets created offline. This might lead to non-discriminative visual words and, as a consequence, to poor recognition performance. This paper proposes a visual object recognition system which concurrently learns in an incremental and online fashion both the visual object category representations as well as the codebook words used to encode them. The codebook is defined using Gaussian Mixture Models which are updated using new object views. The approach contains similarities with the human visual object recognition system: evidence suggests that the development of recognition capabilities occurs on multiple levels and is sustained over large periods of time. Results show that the proposed system with concurrent learning of object categories and codebooks is capable of learning more categories, requiring less examples, and with similar accuracies, when compared to the classical Bag of Words approach using codebooks constructed offline. | ||||
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| Publisher | IEEE | Place of Publication | Hamburg, Germany | Editor | |
| Language | English | Summary Language | English | Original Title | |
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| Area | Expedition | Conference | 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) | ||
| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 41 | ||
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| Author | Patricia Súarez, Henry Velesaca, Dario Carpio & Angel Sappa | ||||
| Title |
Corn Kernel Classification From Few Training Samples | Type | Journal Article | ||
| Year | 2023 | Publication | In journal Artificial Intelligence in Agriculture | Abbreviated Journal | |
| Volume | Vol. 9 | Issue | Pages | pp. 89-99 | |
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| ISSN | 25897217 | ISBN | Medium | ||
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 223 | ||
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| Author | Jacome-Galarza L.-R | ||||
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Crop yield prediction utilizing multimodal deep learning | Type | Conference Article | ||
| Year | 2021 | Publication | 16th Iberian Conference on Information Systems and Technologies, CISTI 2021, junio 23 – 26, 2021 | Abbreviated Journal | |
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| Keywords | Agricultura de precisión; sensores remotos; aprendizaje profundo multimodal; IoT; agentes inteligentes; computación aplicada. | ||||
| Abstract | La agricultura de precisión es una práctica vital para mejorar la producción de cosechas. El presente trabajo tiene como objetivo desarrollar un modelo multimodal de aprendizaje profundo que es capaz de producir un mapa de salud de cosechas. El modelo recibe como entradas imágenes multiespectrales y datos de sensores de campo (humedad, temperatura, estado del suelo, etc.) y crea un mapa de rendimiento de la cosecha. La utilización de datos multimodales tiene como finalidad extraer patrones ocultos del estado de salud de las cosechas y de esta manera obtener mejores resultados que los obtenidos mediante los índices de vegetación. |
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| Language | Español | Summary Language | Original Title | ||
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| Call Number | cidis @ cidis @ | Serial | 150 | ||
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| Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla | ||||
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Cross-spectral image dehaze through a dense stacked conditional GAN based approach. | Type | Conference Article | ||
| Year | 2018 | Publication | 14th IEEE International Conference on Signal Image Technology & Internet based Systems (SITIS 2018) | Abbreviated Journal | |
| Volume | Issue | Pages | 358-364 | ||
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| Abstract | This paper proposes a novel approach to remove haze from RGB images using a near infrared images based on a dense stacked conditional Generative Adversarial Network (CGAN). The architecture of the deep network implemented receives, besides the images with haze, its corresponding image in the near infrared spectrum, which serve to accelerate the learning process of the details of the characteristics of the images. The model uses a triplet layer that allows the independence learning of each channel of the visible spectrum image to remove the haze on each color channel separately. A multiple loss function scheme is proposed, which ensures balanced learning between the colors and the structure of the images. Experimental results have shown that the proposed method effectively removes the haze from the images. Additionally, the proposed approach is compared with a state of the art approach showing better results. | ||||
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| Notes | Approved | no | |||
| Call Number | gtsi @ user @ | Serial | 92 | ||
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| Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla | ||||
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Cross-spectral Image Patch Similarity using Convolutional Neural Network | Type | Conference Article | ||
| Year | 2017 | Publication | 2017 IEEE International Workshop of Electronics, Control, Measurement, Signals and their application to Mechatronics (ECMSM) | Abbreviated Journal | |
| Volume | Issue | Pages | 1-5 | ||
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| Call Number | cidis @ cidis @ | Serial | 57 | ||
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| Author | Mildred Cruz; Cristhian A. Aguilera; Boris X. Vintimilla; Ricardo Toledo; Ángel D. Sappa | ||||
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Cross-spectral image registration and fusion: an evaluation study | Type | Conference Article | ||
| Year | 2015 | Publication | 2nd International Conference on Machine Vision and Machine Learning | Abbreviated Journal | |
| Volume | 331 | Issue | Pages | ||
| Keywords | multispectral imaging; image registration; data fusion; infrared and visible spectra | ||||
| Abstract | This paper presents a preliminary study on the registration and fusion of cross-spectral imaging. The objective is to evaluate the validity of widely used computer vision approaches when they are applied at different spectral bands. In particular, we are interested in merging images from the infrared (both long wave infrared: LWIR and near infrared: NIR) and visible spectrum (VS). Experimental results with different data sets are presented. | ||||
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| Publisher | Computer Vision Center | Place of Publication | Barcelona, Spain | Editor | |
| Language | English | Summary Language | English | Original Title | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 35 | ||
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| Author | Rafael Rivadeneira, Henry Velesaca & Angel Sappa | ||||
| Title |
Cross-Spectral Image Registration: a Comparative Study and a New Benchmark Dataset | Type | Conference Article | ||
| Year | 2024 | Publication | In Fourth International Conference on Innovations in Computational Intelligence and Computer Vision (ICICV 2024) | Abbreviated Journal | |
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| Call Number | cidis @ cidis @ | Serial | 237 | ||
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| Author | Cristhian A. Aguilera; Angel D. Sappa; Ricardo Toledo | ||||
| Title |
Cross-Spectral Local Descriptors via Quadruplet Network | Type | Journal Article | ||
| Year | 2017 | Publication | In Sensors Journal | Abbreviated Journal | |
| Volume | Vol. 17 | Issue | Pages | pp. 873 | |
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| Call Number | gtsi @ user @ | Serial | 64 | ||
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| Author | N. Onkarappa; Cristhian A. Aguilera; B. X. Vintimilla; Angel D. Sappa | ||||
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Cross-spectral Stereo Correspondence using Dense Flow Fields | Type | Conference Article | ||
| Year | 2014 | Publication | Computer Vision Theory and Applications (VISAPP), 2014 International Conference on, Lisbon, Portugal, 2014 | Abbreviated Journal | |
| Volume | 3 | Issue | Pages | 613 - 617 | |
| Keywords | Cross-spectral Stereo Correspondence, Dense Optical Flow, Infrared and Visible Spectrum | ||||
| Abstract | 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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| Publisher | IEEE | Place of Publication | Editor | ||
| Language | English | Summary Language | English | Original Title | |
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| Area | Expedition | Conference | 2014 International Conference on Computer Vision Theory and Applications (VISAPP) | ||
| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 27 | ||
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