| Records |
| Author |
Wassim El Ahmar, Angel D. Sappa and Riad Hammoud |
| Title |
Thermal Pedestrian MultipleObject Tracking Challenge (TPMOT) |
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Conference Article |
| Year |
2025 |
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IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops CVPRW 2025 |
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no |
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cidis @ cidis @ |
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275 |
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| Author |
Nathan Inkawhich, Claire Thorp, Justice Wheelwright, Oliver Nina, Dylan Bowald, Angel Sappa, Erik Blasch |
| Title |
4th Multi-modal Aerial View Image Challenge: SAR CLASSIFICATION – PBVS 2025 |
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Journal Article |
| Year |
2025 |
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IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops CVPRW 2025 |
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no |
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cidis @ cidis @ |
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276 |
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Dylan Bowald, Justice Wheelwright, Oliver Nina, Angel Sappa, Riad Hammoud, Erik Blasch, Nathan Inkawhich |
| Title |
3th Multi-modal Aerial View Image Challenge: Sensor Domain Translation – PBVS 2025 |
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Conference Article |
| Year |
2025 |
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IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops CVPRW 2025 |
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no |
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cidis @ cidis @ |
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277 |
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| Author |
Patricia Suarez & Angel D. Sappa |
| Title |
Lightweight Architecture for Fruit Quality Estimation in the Infrared Domain |
Type |
Conference Article |
| Year |
2025 |
Publication |
5th International Conference on Innovations in Computational Intelligence and Computer Vision ICICV 2025 |
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no |
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cidis @ cidis @ |
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278 |
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| Author |
Henry O. Velesaca Hector Villegas, and Angel D. Sappa |
| Title |
Exploring Camouflaged Object Detection Techniques for Invasive Vegetation Monitoring |
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Conference Article |
| Year |
2025 |
Publication |
14th International Conference on Data Science, Technology and Applications DATA 2025 |
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no |
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cidis @ cidis @ |
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279 |
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| Author |
Kevin E. Munoz, Loberlly N. Salazar, Steven S. Araujo, and Boris X. Vintimilla |
| Title |
Stereo Vision Techniques: A Comparative Study of Traditional and Machine Learning-Based Approaches |
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Conference Article |
| Year |
2025 |
Publication |
5th International Conference on Computer Vision and Robotics CVR 2025 |
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no |
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cidis @ cidis @ |
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280 |
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| Author |
Kevin E. Muñoz Loberlly N. Salazar Steven S. Araujo Boris X. Vintimilla |
| Title |
Detecting and Characterizing Human Interactions to EnhanceHuman-Robot Engagement |
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Conference Article |
| Year |
2025 |
Publication |
3rd International Conference on Robotics, Control and Vision Engineering RCVE 2025 |
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no |
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cidis @ cidis @ |
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281 |
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| Author |
Marjorie Chalen; Boris X. Vintimilla |
| Title |
Towards Action Prediction Applying Deep Learning |
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Journal Article |
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2019 |
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Latin American Conference on Computational Intelligence (LA-CCI); Guayaquil, Ecuador; 11-15 Noviembre 2019 |
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pp. 1-3 |
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action prediction, early recognition, early detec- tion, action anticipation, cnn, deep learning, rnn, lstm. |
| Abstract |
Considering the incremental development future action prediction by video analysis task of computer vision where it is done based upon incomplete action executions. Deep learning is playing an important role in this task framework. Thus, this paper describes recently techniques and pertinent datasets utilized in human action prediction task. |
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no |
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cidis @ cidis @ |
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129 |
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| Author |
Jacome-Galarza L.-R |
| Title |
Crop yield prediction utilizing multimodal deep learning |
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Conference Article |
| Year |
2021 |
Publication |
16th Iberian Conference on Information Systems and Technologies, CISTI 2021, junio 23 – 26, 2021 |
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Agricultura de precisión; sensores remotos; aprendizaje profundo multimodal; IoT; agentes inteligentes; computación aplicada. |
| Abstract |
La agricultura de precisión es una práctica vital para
mejorar la producción de cosechas. El presente trabajo tiene
como objetivo desarrollar un modelo multimodal de aprendizaje
profundo que es capaz de producir un mapa de salud de
cosechas. El modelo recibe como entradas imágenes multiespectrales
y datos de sensores de campo (humedad,
temperatura, estado del suelo, etc.) y crea un mapa de
rendimiento de la cosecha. La utilización de datos multimodales
tiene como finalidad extraer patrones ocultos del estado de salud
de las cosechas y de esta manera obtener mejores resultados que
los obtenidos mediante los índices de vegetación. |
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Español |
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Approved |
no |
| Call Number |
cidis @ cidis @ |
Serial |
150 |
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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 |
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2488 - 2495 |
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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. |
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IEEE |
Place of Publication |
Hamburg, Germany |
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English |
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English |
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2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) |
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Approved |
no |
| Call Number |
cidis @ cidis @ |
Serial |
41 |
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