| Records |
| Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla |
| Title |
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” ) |
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2017-July |
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212-217 |
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no |
| Call Number |
cidis @ cidis @ |
Serial |
62 |
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| Author |
Henry O. Velesaca, Juan Antonio Holgado-Terriza, Doménica Carrasco, José Miguel Gutiérrez Guerrero, Tonny Toscano, Darío Carpio & Angel Sappa |
| Title |
Anomaly Detection in Industrial Production Products using OPC-UA and Deep Learning |
Type |
Conference Article |
| Year |
2024 |
Publication |
13th International Conference on Data Science, Technology and Applications, DATA 2024 Dijon 9-11 July 2024 |
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505 - 512 |
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978-989758707-8 |
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no |
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cidis @ cidis @ |
Serial |
232 |
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| Author |
Xavier Soria; Angel D. Sappa |
| Title |
Improving Edge Detection in RGB Images by Adding NIR Channel. |
Type |
Conference Article |
| Year |
2018 |
Publication |
14th IEEE International Conference on Signal Image Technology & Internet based Systems (SITIS 2018) |
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Pages |
266-273 |
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no |
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gtsi @ user @ |
Serial |
95 |
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| Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla |
| Title |
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) |
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Issue |
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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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no |
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gtsi @ user @ |
Serial |
92 |
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| Author |
Jorge L. Charco; Boris X. Vintimilla; Angel D. Sappa |
| Title |
Deep learning based camera pose estimation in multi-view environment. |
Type |
Conference Article |
| Year |
2018 |
Publication |
14th IEEE International Conference on Signal Image Technology & Internet based Systems (SITIS 2018) |
Abbreviated Journal |
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Issue |
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Pages |
224-228 |
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| Abstract |
This paper proposes to use a deep learning network architecture for relative camera pose estimation on a multi-view environment. The proposed network is a variant architecture of AlexNet to use as regressor for prediction the relative translation and rotation as output. The proposed approach is trained from scratch on a large data set that takes as input a pair of images from the same scene. This new architecture is compared with a previous approach using standard metrics, obtaining better results on the relative camera pose. |
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Approved |
no |
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gtsi @ user @ |
Serial |
93 |
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| Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud |
| Title |
Deep Learning based Single Image Dehazing |
Type |
Conference Article |
| Year |
2018 |
Publication |
14th IEEE Workshop on Perception Beyond the Visible Spectrum – In conjunction with CVPR 2018. Salt Lake City, Utah. USA |
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This paper proposes a novel approach to remove haze
degradations in RGB images using a stacked conditional
Generative Adversarial Network (GAN). It employs a triplet
of GAN to remove the haze on each color channel independently.
A multiple loss functions scheme, applied over a
conditional probabilistic model, is proposed. The proposed
GAN architecture learns to remove the haze, using as conditioned
entrance, the images with haze from which the clear
images will be obtained. Such formulation ensures a fast
model training convergence and a homogeneous model generalization.
Experiments showed that the proposed method
generates high-quality clear images. |
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no |
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gtsi @ user @ |
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83 |
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| Author |
Omar Coello, Moisés Coronel, Darío Carpio, Boris X. Vintimilla & Luis Chuquimarca |
| Title |
Enhancing Apple’s Defect Classification: Insights from Visible Spectrum and Narrow Spectral Band Imaging |
Type |
Conference Article |
| Year |
2024 |
Publication |
14th International Conference on Pattern Recognition Systems (ICPRS) Londres 15 – 18 July 2024 |
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979-835037565-7 |
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Approved |
no |
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cidis @ cidis @ |
Serial |
244 |
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| Author |
Luis Chuquimarca, Boris X. Vintimilla & Sergio Velastin |
| Title |
Classifying Healthy and Defective Fruits with a Multi-Input Architecture and CNN Models |
Type |
Conference Article |
| Year |
2024 |
Publication |
14th International Conference on Pattern Recognition Systems (ICPRS) Londres 15 – 18 July 2024 |
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979-835037565-7 |
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Approved |
no |
| Call Number |
cidis @ cidis @ |
Serial |
245 |
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| Author |
Patricia Suarez, Angel Sappa |
| Title |
Depth-Conditioned Thermal-like Image Generation |
Type |
Conference Article |
| Year |
2024 |
Publication |
14th International Conference on Pattern Recognition Systems (ICPRS) Londres 15 – 18 July 2024 |
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979-835037565-7 |
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Approved |
no |
| Call Number |
cidis @ cidis @ |
Serial |
243 |
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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 |
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no |
| Call Number |
cidis @ cidis @ |
Serial |
58 |
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