Listar AC - Contribuciones a congresos científicos por autor "Guil-Mata, Nicolás"
Mostrando ítems 1-16 de 16
-
A Framework For TV Logos Learning Using Linear Inverse Diffusion Filters For Noise Removal
Ramos-Cózar, Julián
; Zeljković, Vesna; González-Linares, José María; Guil-Mata, Nicolás; Tameze, Claude; Valev, Ventzeslav[et al.] (IEEE, 2013)
Different logotypes represent significant cues for video annotations. A combination of temporal and spatial segmentation methods can be used for logo extraction from various video contents. To achieve this segmentation, ... -
A Hybrid Piece-Wise Slowdown Model for Concurrent Kernel Execution on GPU
López Albelda, Bernabé; Castro, Francisco M.; González-Linares, José María; Guil-Mata, Nicolás (José Cano, Phil Trinder, 2022-08)
Current execution of kernels on GPUs allows improving the use of hardware resources and reducing the execution time of co-executed kernels. In addition, efficient kernel-oriented scheduling policies pursuing criteria based ... -
CUVLE: Variable-Length Encoding on CUDA
Fuentes-Alventosa, Antonio; Gómez-Luna, Juan; González-Linares, José María; Guil-Mata, Nicolás (2014-10-14)
Data compression is the process of representing information in a compact form, in order to reduce the storage requirements and, hence, communication bandwidth. It has been one of the critical enabling technologies for ... -
Efficient OpenCL-based concurrent tasks offloading on accelerators
Lázaro-Muñoz, Antonio J.; González-Linares, José María; Gómez-Luna, Juan; Guil-Mata, Nicolás (Procedia Computer Science, 2017)
Current heterogeneous platforms with CPUs and accelerators have the ability to launch several independent tasks simultaneously, in order to exploit concurrency among them. These tasks typically consist of data transfer ... -
End-to-end Incremental Learning
Castro Payán, Francisco Manuel; Marín-Jiménez, Manuel J.; Guil-Mata, Nicolás; Schmid, Cordelia; Alahari, Karteek (2018-07-06)
Although deep learning approaches have stood out in recent years due to their state-of-the-art results, they continue to suffer from (catastrophic forgetting), a dramatic decrease in overall performance when training with ... -
Evaluation of CNN architectures for gait recognition based on optical flow maps
Castro, Francisco M.; Marín-Jiménez, Manuel J.; Guil-Mata, Nicolás; López-Tapia, S.; Pérez de la Blanca, N. (2017)
This work targets people identification in video based on the way they walk (\ie gait) by using deep learning architectures. We explore the use of convolutional neural networks (CNN) for learning high-level descriptors ... -
Gait recognition and fall detection with inertial sensors
Delgado-Escaño, Rubén; Castro, Francisco M.; Marín-Jiménez, Manuel J.; Guil-Mata, Nicolás (2019-11-26)
In contrast to visual information that is recorded by cameras placed somewhere, inertial information can be obtained from mobile phones that are commonly used in daily life. We present in this talk a general deep learning ... -
Gait recognition applying Incremental learning
Castro, Francisco M.; Marín-Jiménez, Manuel J.; Guil-Mata, Nicolás; Schmid, Cordelia; Alahari, Karteek (2019-11-25)
when new knowledge needs to be included in a classifier, the model is retrained from scratch using a huge training set that contains all available information of both old and new knowledge. However, in this talk, we present ... -
Low-textured regions detection for improving stereoscopy algorithms
Ibarra-Delgado, Salvador; Ramos-Cózar, Julián; González-Linares, José María; Gómez Luna, Juan; Guil-Mata, Nicolás (2014-07-29)
The main goal of stereoscopy algorithms is the calculation of the disparity map between two frames corresponding to the same scene, and captured simultaneously by two different cameras. The different position (disparity) ... -
Multimodal Human Pose Feature Fusion for Gait Recognition.
Cubero, Nicolás; Castro Payán, Francisco Manuel; Ramos-Cózar, Julián; Guil-Mata, Nicolás; Marín Jiménez, Manuel Jesús (2023)
Gait recognition allows identifying people at a distance based on the way they walk (i.e. gait) in a non-invasive approach. Most of the approaches published in the last decades are dominated by the use of silhouettes or ... -
Pre-Ictal Phase Detection with SVMs
Ramos-Cózar, Julián; Zeljković, Vesna; González-Linares, José María; Guil-Mata, Nicolás; Bojic, Milena; Valev, Ventzeslav[et al.] (2014-07-29)
Over 50 million persons worldwide are affected by epilepsy. Epilepsy is a brain disorder known for sudden, unexpected transitions from normal to pathological behavioral states called epileptic seizures. Epilepsy poses a ... -
Real-Time Unsupervised Object Localization on the Edge for Airport Video Surveillance.
Object localization is vital in computer vision to solve object detection or classification problems. Typically, this task is performed on expensive GPU devices, but edge computing is gaining importance in real-time ... -
Robust tracking for augmented reality
González-Linares, José María; Guil-Mata, Nicolás; Ramos-Cózar, Julián (2015-06-17)
In this paper a method for improving a tracking algorithm in an augmented reality application is presented. This method addresses several issues to this particular application, like marker-less tracking and color constancy ... -
A scheduling theory framework for GPU tasks efficient execution
Lázaro Muñoz, Antonio José; López Albelda, Bernabé; González-Linares, José María; Guil-Mata, Nicolás (2018-07-16)
Concurrent execution of tasks in GPUs can reduce the computation time of a workload by overlapping data transfer and execution commands. However it is difficult to implement an efficient run- time scheduler ... -
Tasks Fairness Scheduler for GPU
López Albelda, Bernabé; González-Linares, José María; Guil-Mata, Nicolás (2019-09-24)
Nowadays GPU clusters are available in almost every data processing center. Their GPUs are typically shared by different applications that might have different processing needs and/or different levels of priority. As current ... -
A weakly-supervised approach for discovering common objects in airport video surveillance footage
Castro Payán, Francisco Manuel; Delgado-Escaño, Rubén; Guil-Mata, Nicolás; Marín-Jiménez, Manuel J. (2019-07-22)
Object detection in video is a relevant task in computer vision. Standard and current detectors are typically trained in a strongly supervised way, what requires a huge amount of labelled data. In contrast, in this paper ...