Home | << 1 2 3 4 5 6 7 >> |
Records | |||||
---|---|---|---|---|---|
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 | 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 | Issue | Pages | 1-5 | ||
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 | 57 | ||
Permanent link to this record | |||||
Author | Angel J. Valencia; Roger M. Idrovo; Angel D. Sappa; Douglas Plaza G.; Daniel Ochoa | ||||
Title | A 3D Vision Based Approach for Optimal Grasp of Vacuum Grippers | Type | Conference Article | ||
Year | 2017 | Publication | 2017 IEEE International Workshop of Electronics, Control, Measurement, Signals and their application to Mechatronics (ECMSM) | Abbreviated Journal | |
Volume | Issue | Pages | 1-6 | ||
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 | 60 | ||
Permanent link to this record | |||||
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 | ||
Permanent link to this record | |||||
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 | ||
Permanent link to this record | |||||
Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla | ||||
Title | Learning Image Vegetation Index through a Conditional Generative Adversarial Network | Type | Conference Article | ||
Year | 2017 | Publication | 2nd IEEE Ecuador Tehcnnical Chapters Meeting (ETCM) | Abbreviated Journal | |
Volume | Issue | Pages | |||
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 | 70 | ||
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 | 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 | P. Ricaurte; C. Chilán; C. A. Aguilera-Carrasco; B. X. Vintimilla; Angel D. Sappa | ||||
Title | Performance Evaluation of Feature Point Descriptors in the Infrared Domain | Type | Conference Article | ||
Year | 2014 | Publication | Computer Vision Theory and Applications (VISAPP), 2014 International Conference on, Lisbon, Portugal, 2013 | Abbreviated Journal | |
Volume | 1 | Issue | Pages | 545 -550 | |
Keywords | Infrared Imaging, Feature Point Descriptors | ||||
Abstract | This paper presents a comparative evaluation of classical feature point descriptors when they are used in the long-wave infrared spectral band. Robustness to changes in rotation, scaling, blur, and additive noise are evaluated using a state of the art framework. Statistical results using an outdoor image data set are presented together with a discussion about the differences with respect to the results obtained when images from the visible spectrum are considered. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | IEEE | 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 | 2014 International Conference on Computer Vision Theory and Applications (VISAPP) | ||
Notes | Approved | no | |||
Call Number | cidis @ cidis @ | Serial | 26 | ||
Permanent link to this record | |||||
Author | A. Amato; F. Lumbreras; Angel D. Sappa | ||||
Title | A general-purpose crowdsourcing platform for mobile devices | Type | Conference Article | ||
Year | 2014 | Publication | Computer Vision Theory and Applications (VISAPP), 2014 International Conference on, Lisbon, Portugal, 2014 | Abbreviated Journal | |
Volume | 3 | Issue | Pages | 211-215 | |
Keywords | Crowdsourcing Platform, Mobile Crowdsourcing | ||||
Abstract | This paper presents details of a general purpose micro-taskon-demand platform based on the crowdsourcing philosophy. This platformwas specifically developed for mobile devices in order to exploit the strengths of such devices; namely: i) massivity, ii) ubiquityand iii) embedded sensors.The combined use of mobile platforms and the crowdsourcing model allows to tackle from the simplest to the most complex tasks.Users experience is the highlighted feature of this platform (this fact is extended to both task-proposer and task- solver).Proper tools according with a specific task are provided to a task-solver in order to perform his/her job in a simpler, faster and appealing way.Moreover, a task can be easily submitted by just selecting predefined templates, which cover a wide range of possible applications.Examples of its usage in computer vision and computer games are provided illustrating the potentiality of the platform. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | IEEE | Place of Publication | Lisbon, Portugal | 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 | Computer Vision Theory and Applications (VISAPP), 2014 International Conference on | ||
Notes | Approved | no | |||
Call Number | cidis @ cidis @ | Serial | 25 | ||
Permanent link to this record |