| Records |
| Author |
Juan A. Carvajal; Dennis G. Romero; Angel D. Sappa |
| Title |
Fine-tuning deep convolutional networks for lepidopterous genus recognition |
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Journal Article |
| Year |
2017 |
Publication |
Lecture Notes in Computer Science |
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Vol. 10125 LNCS |
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pp. 467-475 |
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63 |
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| Author |
Cristhian A. Aguilera; Angel D. Sappa; Ricardo Toledo |
| Title |
Cross-Spectral Local Descriptors via Quadruplet Network |
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Journal Article |
| Year |
2017 |
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In Sensors Journal |
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Vol. 17 |
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pp. 873 |
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no |
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64 |
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| Author |
Victor Santos; Angel D. Sappa; Miguel Oliveira |
| Title |
Special Issue on Autonomous Driving an Driver Assistance Systems |
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Journal Article |
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2017 |
Publication |
In Robotics and Autonomous Systems Journal |
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Vol. 91 |
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pp. 208-209 |
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65 |
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| Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla |
| Title |
Colorizing Infrared Images through a Triplet Condictional DCGAN Architecture |
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Conference Article |
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2017 |
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19th International Conference on Image Analysis and Processing. |
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287-297 |
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no |
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66 |
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| Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla |
| Title |
Learning Image Vegetation Index through a Conditional Generative Adversarial Network |
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Conference Article |
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2017 |
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2nd IEEE Ecuador Tehcnnical Chapters Meeting (ETCM) |
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no |
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gtsi @ user @ |
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70 |
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| Author |
Lukas Danev; Marten Hamann; Nicolas Fricke; Tobias Hollarek; Dennys Paillacho |
| Title |
Development of animated facial expression to express emotions in a robot: RobotIcon. |
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Conference Article |
| Year |
2017 |
Publication |
IEEE Ecuador Technical Chapter Meeting (ETCM) |
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2017-January |
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1-6 |
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no |
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71 |
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| Author |
Xavier Soria; Angel D. Sappa; Arash Akbarinia |
| Title |
Multispectral Single-Sensor RGB-NIR Imaging: New Challenges an Oppotunities |
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Conference Article |
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2017 |
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The 7th International Conference on Image Processing Theory, Tools and Application |
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1-6 |
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no |
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gtsi @ user @ |
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72 |
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| Author |
Milton Mendieta; F. Panchana; B. Andrade; B. Bayot; C. Vaca; Boris X. Vintimilla; Dennis G. Romero |
| Title |
Organ identification on shrimp histological images: A comparative study considering CNN and feature engineering. |
Type |
Conference Article |
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2018 |
Publication |
IEEE Ecuador Technical Chapters Meeting ETCM 2018. Cuenca, Ecuador |
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1-6 |
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The identification of shrimp organs in biology using
histological images is a complex task. Shrimp histological images
poses a big challenge due to their texture and similarity among
classes. Image classification by using feature engineering and
convolutional neural networks (CNN) are suitable methods to
assist biologists when performing organ detection. This work
evaluates the Bag-of-Visual-Words (BOVW) and Pyramid-Bagof-
Words (PBOW) models for image classification leveraging big
data techniques; and transfer learning for the same classification
task by using a pre-trained CNN. A comparative analysis
of these two different techniques is performed, highlighting
the characteristics of both approaches on the shrimp organs
identification problem. |
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no |
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gtsi @ user @ |
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87 |
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| Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud |
| Title |
Deep Learning based Single Image Dehazing |
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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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Approved |
no |
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gtsi @ user @ |
Serial |
83 |
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| Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud |
| Title |
Near InfraRed Imagery Colorization |
Type |
Conference Article |
| Year |
2018 |
Publication |
25 th IEEE International Conference on Image Processing, ICIP 2018 |
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2237-2241 |
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This paper proposes a stacked conditional Generative
Adversarial Network-based method for Near InfraRed
(NIR) imagery colorization. We propose a variant architecture
of Generative Adversarial Network (GAN) that uses multiple
loss functions over a conditional probabilistic generative model.
We show that this new architecture/loss-function yields better
generalization and representation of the generated colored IR
images. The proposed approach is evaluated on a large test
dataset and compared to recent state of the art methods using
standard metrics.1
Index Terms—Convolutional Neural Networks (CNN), Generative
Adversarial Network (GAN), Infrared Imagery colorization. |
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no |
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gtsi @ user @ |
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81 |
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