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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) Abbreviated Journal
Volume (down) 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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Call Number gtsi @ user @ Serial 92
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Author Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla
Title 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 (down) Issue Pages 1-5
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Call Number cidis @ cidis @ Serial 57
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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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Call Number cidis @ cidis @ Serial 58
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Author Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud
Title Image Vegetation Index through a Cycle Generative Adversarial Network Type Conference Article
Year 2019 Publication Conference on Computer Vision and Pattern Recognition Workshops (CVPR 2019); Long Beach, California, United States Abbreviated Journal
Volume (down) Issue Pages 1014-1021
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Abstract This paper proposes a novel approach to estimate the

Normalized Difference Vegetation Index (NDVI) just from

an RGB image. The NDVI values are obtained by using

images from the visible spectral band together with a synthetic near infrared image obtained by a cycled GAN. The

cycled GAN network is able to obtain a NIR image from

a given gray scale image. It is trained by using unpaired

set of gray scale and NIR images by using a U-net architecture and a multiple loss function (gray scale images are

obtained from the provided RGB images). Then, the NIR

image estimated with the proposed cycle generative adversarial network is used to compute the NDVI index. Experimental results are provided showing the validity of the proposed approach. Additionally, comparisons with previous

approaches are also provided.
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Call Number gtsi @ user @ Serial 106
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Author Rafael E. Rivadeneira; Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla.
Title Thermal Image SuperResolution through Deep Convolutional Neural Network. Type Conference Article
Year 2019 Publication 16th International Conference on Image Analysis and Recognition (ICIAR 2019); Waterloo, Canadá Abbreviated Journal
Volume (down) Issue Pages 417-426
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Abstract Due to the lack of thermal image datasets, a new dataset has been acquired for proposed a superesolution approach using a Deep Convolution Neural Network schema. In order to achieve this image enhancement process a new thermal images dataset is used. Di?erent experiments have been carried out, ?rstly, the proposed architecture has been trained using only images of the visible spectrum, and later it has been trained with images of the thermal spectrum, the results showed that with the network trained with thermal images, better results are obtained in the process of enhancing the images, maintaining the image details and perspective. The thermal dataset is available at http://www.cidis.espol.edu.ec/es/dataset
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Call Number gtsi @ user @ Serial 103
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Author Raul A. Mira; Patricia L. Suarez; Rafael E. Rivadeneira; Angel D. Sappa
Title PETRA: A Crowdsourcing-Based Platform for Rocks Data Collection and Characterization Type Conference Article
Year 2019 Publication IEEE ETCM 2019 Fourth Ecuador Technical Chapters Meeting; Guayaquil, Ecuador Abbreviated Journal
Volume (down) Issue Pages 1-6
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Abstract This paper presents details of a distributed platform intended for data acquisition, evaluation, storage and visualization, which is fully implemented under the crowdsourcing paradigm. The proposed platform is the result from collaboration between computer science and petrology researchers and it is intended for academic purposes. The platform is designed within a MTV (Model, Template and View) architecture and also designed for a collaborative data store and managing of rocks from multiple readers and writers, taking advantage of ubiquity of web applications, and neutrality of researchers from different

communities to validate the data. The platform is being used and validated by students and academics from our university; in the near future it will be open to other users interested on this topic.
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Call Number gtsi @ user @ Serial 112
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Author Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla
Title Image patch similarity through a meta-learning metric based approach Type Conference Article
Year 2019 Publication 15th International Conference on Signal Image Technology & Internet based Systems (SITIS 2019); Sorrento, Italia Abbreviated Journal
Volume (down) Issue Pages 511-517
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Abstract 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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Call Number gtsi @ user @ Serial 115
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Author Patricia L. Suarez
Title Procesamiento y representación de imágenes multiespectrales usando técnicas de aprendizaje profundo (Ph.D. Angel Sappa, Director & Ph.D. Boris Vintimilla, Codirector.). Ph.D. thesis. Type Book Chapter
Year 2020 Publication Ediciones FIEC-ESPOL. Abbreviated Journal
Volume (down) Issue Pages
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Corporate Author Ph.D. Angel Sappa, Director & Ph.D. Boris Vintimilla, Codirector. Thesis
Publisher Place of Publication Editor
Language Español Summary Language Original Title
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Call Number cidis @ cidis @ Serial 144
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Author Patricia L. Suarez, Dario Carpio, Angel D. Sappa and Henry O. Velesaca
Title Transformer based Image Dehazing. Type Conference Article
Year 2022 Publication 16TH International Conference On Signal Image Technology & Internet Based Systems SITIS 2022. Abbreviated Journal
Volume (down) Issue Pages 148-154
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Call Number cidis @ cidis @ Serial 195
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Author Patricia L. Suarez, Dario Carpio, Angel Sappa
Title Boosting Guided Super-Resolution Performance with Synthesized Images Type Conference Article
Year 2023 Publication 17th International Conference On Signal Image Technology & Internet Based Systems Abbreviated Journal
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Notes Approved no
Call Number cidis @ cidis @ Serial 225
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