CIDIS - Publicaciones -- Query Results

	CIDIS - Publicaciones Home \| Show All \| Simple Search \| Advanced Search	Login Quick Search: Field: contains: ...
	11–20 of 41 records found matching your query (RSS):

Search & Display Options

Select All Deselect All

<< 1 2 3 4 5 >>

List View

Citations

Details

	Records
	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		Issue		Pages	417-426
	Keywords
	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
	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	103
Permanent link to this record



	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		Issue		Pages	358-364
	Keywords
	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.
	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	92
Permanent link to this record



	Author	Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla
	Title	Vegetation Index Estimation from Monospectral Images			Type	Conference Article
	Year	2018	Publication	15th International Conference, Image Analysis and Recognition (ICIAR 2018), Póvoa de Varzim, Portugal. Lecture Notes in Computer Science	Abbreviated Journal
	Volume	10882	Issue		Pages	353-362
	Keywords
	Abstract	This paper proposes a novel approach to estimate Normalized Difference Vegetation Index (NDVI) from just the red channel of a RGB image. The NDVI index is defined as the ratio of the difference of the red and infrared radiances over their sum. In other words, information from the red channel of a RGB image and the corresponding infrared spectral band are required for its computation. In the current work the NDVI index is estimated just from the red channel by training a Conditional Generative Adversarial Network (CGAN). The architecture proposed for the generative network consists of a single level structure, which combines at the final layer results from convolutional operations together with the given red channel with Gaussian noise to enhance details, resulting in a sharp NDVI image. Then, the discriminative model estimates the probability that the NDVI generated index came from the training dataset, rather than the index automatically generated. Experimental results with a large set of real images are provided showing that a Conditional GAN single level model represents an acceptable approach to estimate NDVI index.
	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	82
Permanent link to this record



	Author	Rafael E. Rivadeneira, Angel D. Sappa, Boris X. Vintimilla, Jin Kim, Dogun Kim et al.
	Title	Thermal Image Super-Resolution Challenge Results- PBVS 2022.			Type	Conference Article
	Year	2022	Publication	Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24.	Abbreviated Journal	CONFERENCE
	Volume	2022-June	Issue		Pages	349-357
	Keywords
	Abstract	This paper presents results from the third Thermal Image Super-Resolution (TISR) challenge organized in the Perception Beyond the Visible Spectrum (PBVS) 2022 workshop. The challenge uses the same thermal image dataset as the first two challenges, with 951 training images and 50 validation images at each resolution. A set of 20 images was kept aside for testing. The evaluation tasks were to measure the PSNR and SSIM between the SR image and the ground truth (HR thermal noisy image downsampled by four), and also to measure the PSNR and SSIM between the SR image and the semi-registered HR image (acquired with another camera). The results outperformed those from last year’s challenge, improving both evaluation metrics. This year, almost 100 teams participants registered for the challenge, showing the community’s interest in this hot topic.
	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	175
Permanent link to this record



	Author	Dennis G. Romero; A. Frizera; Angel D. Sappa; Boris X. Vintimilla; T.F. Bastos
	Title	A predictive model for human activity recognition by observing actions and context			Type	Conference Article
	Year	2015	Publication	ACIVS 2015 (Advanced Concepts for Intelligent Vision Systems), International Conference on, Catania, Italy, 2015	Abbreviated Journal
	Volume		Issue		Pages	323 - 333
	Keywords	Edge width, Image blu,r Defocus map, Edge model
	Abstract	This paper presents a novel model to estimate human activities – a human activity is defined by a set of human actions. The proposed approach is based on the usage of Recurrent Neural Networks (RNN) and Bayesian inference through the continuous monitoring of human actions and its surrounding environment. In the current work human activities are inferred considering not only visual analysis but also additional resources; external sources of information, such as context information, are incorporated to contribute to the activity estimation. The novelty of the proposed approach lies in the way the information is encoded, so that it can be later associated according to a predefined semantic structure. Hence, a pattern representing a given activity can be defined by a set of actions, plus contextual information or other kind of information that could be relevant to describe the activity. Experimental results with real data are provided showing the validity of 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	43
Permanent link to this record



	Author	Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla
	Title	Colorizing Infrared Images through a Triplet Condictional DCGAN Architecture			Type	Conference Article
	Year	2017	Publication	19th International Conference on Image Analysis and Processing.	Abbreviated Journal
	Volume		Issue		Pages	287-297
	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	66
Permanent link to this record



	Author	Miguel Realpe; Boris X. Vintimilla; L. Vlacic
	Title	Towards Fault Tolerant Perception for autonomous vehicles: Local Fusion.			Type	Conference Article
	Year	2015	Publication	IEEE 7th International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), Siem Reap, 2015.	Abbreviated Journal
	Volume		Issue		Pages	253-258
	Keywords
	Abstract	Many robust sensor fusion strategies have been developed in order to reliably detect the surrounding environments of an autonomous vehicle. However, in real situations there is always the possibility that sensors or other components may fail. Thus, internal modules and sensors need to be monitored to ensure their proper function. This paper introduces a general view of a perception architecture designed to detect and classify obstacles in an autonomous vehicle's environment using a fault tolerant framework, whereas elaborates the object detection and local fusion modules proposed in order to achieve the modularity and real-time process required by the system.
	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	37
Permanent link to this record



	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
	Volume		Issue		Pages	224-228
	Keywords
	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.
	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	93
Permanent link to this record



	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” )	Abbreviated Journal
	Volume	2017-July	Issue		Pages	212-217
	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	62
Permanent link to this record



	Author	Patricia L. Suárez, Angel D. Sappa and Boris X. Vintimilla
	Title	Deep learning-based vegetation index estimation			Type	Book Chapter
	Year	2021	Publication	Generative Adversarial Networks for Image-to-Image Translation Book.	Abbreviated Journal
	Volume	Chapter 9	Issue	Issue 2	Pages	205-232
	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	137
Permanent link to this record