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	Author	Armin Mehri, Parichehr Behjati, Dario Carpio, and Angel D. Sappa
	Title	SRFormer: Efficient Yet Powerful Transformer Network For Single Image Super Resolution			Type	Journal Article
	Year	2023	Publication	IEEE access	Abbreviated Journal
	Volume	Vol. 11	Issue		Pages	121457 - 121469
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	21693536	ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	cidis @ cidis @			Serial	227
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	Author	Ricaurte P; Chilán C; Cristhian A. Aguilera; Boris X. Vintimilla; Angel D. Sappa
	Title	Feature Point Descriptors: Infrared and Visible Spectra			Type	Journal Article
	Year	2014	Publication	Sensors Journal	Abbreviated Journal
	Volume	Vol. 14	Issue		Pages	pp. 3690-3701
	Keywords	cross-spectral imaging; feature point descriptors
	Abstract	This manuscript evaluates the behavior of classical feature point descriptors when they are used in images from long-wave infrared spectral band and compare them with the results obtained in the visible spectrum. Robustness to changes in rotation, scaling, blur, and additive noise are analyzed using a state of the art framework. Experimental results using a cross-spectral outdoor image data set are presented and conclusions from these experiments are given.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	cidis @ cidis @			Serial	28
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	Author	Patricia L. Suárez, Angel D. Sappa, Boris X. Vintimilla
	Title	Cycle generative adversarial network: towards a low-cost vegetation index estimation			Type	Conference Article
	Year	2021	Publication	IEEE International Conference on Image Processing (ICIP 2021)	Abbreviated Journal
	Volume	2021-September	Issue		Pages	2783-2787
	Keywords	CyclicGAN, NDVI, near infrared spectra, instance normalization.
	Abstract	This paper presents a novel unsupervised approach to estimate the Normalized Difference Vegetation Index (NDVI).The NDVI is obtained as the ratio between information from the visible and near infrared spectral bands; in the current work, the NDVI is estimated just from an image of the visible spectrum through a Cyclic Generative Adversarial Network (CyclicGAN). This unsupervised architecture learns to estimate the NDVI index by means of an image translation between the red channel of a given RGB image and the NDVI unpaired index’s image. The translation is obtained by means of a ResNET architecture and a multiple loss function. Experimental results obtained with this unsupervised scheme show the validity of the implemented model. Additionally, comparisons with the state of the art approaches are provided showing improvements with the proposed approach.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	cidis @ cidis @			Serial	164
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	Author	M. Oliveira; L. Seabra Lopes; G. Hyun Lim; S. Hamidreza Kasaei; Angel D. Sappa; A. Tomé
	Title	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.
	Address
	Corporate Author				Thesis
	Publisher	IEEE	Place of Publication	Hamburg, Germany	Editor
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	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 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	Abbreviated Journal
	Volume		Issue		Pages	2237-2241
	Keywords
	Abstract	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.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	gtsi @ user @			Serial	81
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	Author	Xavier Soria; Edgar Riba; Angel D. Sappa
	Title	Dense Extreme Inception Network: Towards a Robust CNN Model for Edge Detection			Type	Conference Article
	Year	2020	Publication	2020 IEEE Winter Conference on Applications of Computer Vision (WACV)	Abbreviated Journal
	Volume		Issue	9093290	Pages	1912-1921
	Keywords
	Abstract	This paper proposes a Deep Learning based edge de- tector, which is inspired on both HED (Holistically-Nested Edge Detection) and Xception networks. The proposed ap- proach generates thin edge-maps that are plausible for hu- man eyes; it can be used in any edge detection task without previous training or fine tuning process. As a second contri- bution, a large dataset with carefully annotated edges, has been generated. This dataset has been used for training the proposed approach as well the state-of-the-art algorithms for comparisons. Quantitative and qualitative evaluations have been performed on different benchmarks showing im- provements with the proposed method when F-measure of ODS and OIS are considered.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-172816553-0	Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	cidis @ cidis @			Serial	126
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	Author	Xavier Soria, Yachuan Li, Mohammad Rouhani & Angel D. Sappa
	Title	Tiny and Efficient Model for the Edge Detection Generalization			Type	Conference Article
	Year	2023	Publication	Proceedings – 2023 IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2023	Abbreviated Journal
	Volume		Issue		Pages	1356 - 1365
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	cidis @ cidis @			Serial	229
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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		Issue		Pages	1014-1021
	Keywords
	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.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	gtsi @ user @			Serial	106
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	Author	Armin Mehri; Angel D. Sappa
	Title	Colorizing Near Infrared Images through a Cyclic Adversarial Approach of Unpaired Samples			Type	Conference Article
	Year	2019	Publication	Conference on Computer Vision and Pattern Recognition Workshops (CVPR 2019); Long Beach, California, United States	Abbreviated Journal
	Volume		Issue		Pages	971-979
	Keywords
	Abstract	This paper presents a novel approach for colorizing near infrared (NIR) images. The approach is based on image-to-image translation using a Cycle-Consistent adversarial network for learning the color channels on unpaired dataset. This architecture is able to handle unpaired datasets. The approach uses as generators tailored networks that require less computation times, converge faster and generate high quality samples. The obtained results have been quantitatively—using standard evaluation metrics—and qualitatively evaluated showing considerable improvements with respect to the state of the art
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	gtsi @ user @			Serial	105
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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
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	gtsi @ user @			Serial	64
Permanent link to this record