Listar por autor "Guil-Mata, Nicolás"
Mostrando ítems 1-20 de 40
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A cross-dataset deep learning-based classifier for people fall detection and identification
Delgado-Escaño, Rubén; Castro, Francisco M.; Ramos-Cózar, Julián
; Marín-Jiménez, Manuel J.; Guil-Mata, Nicolás; Casilari-Pérez, Eduardo[et al.] (Elsevier, 2020)
This paper addresses the issue of fall detection, particularly for elderly individuals who may live alone and be unable to call for help after a fall. The objective is to develop a deep learning-based approach that can ... -
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 ... -
An End-to-End Multi-Task and Fusion CNN for Inertial-Based Gait Recognition.
Delgado-Escaño, Rubén; Castro, Francisco M.; Ramos-Cózar, Julián; Marín Jiménez, Manuel Jesús; Guil-Mata, Nicolás (IEEE, 2019)
People identification using gait information (i.e., the way a person walks) obtained from inertial sensors is a robust approach that can be used in multiple situations where vision-based systems are not applicable. Typically, ... -
Artificial intelligence to assist specialists in the detection of haematological diseases
Díaz-del-Pino, Sergio; Trelles-Martínez, Roberto; González-Fernández, F.A.; Guil-Mata, Nicolás (Elsevier, 2023)
Artificial intelligence, particularly the growth of neural network research and development, has become an invaluable tool for data analysis, offering unrivalled solutions for image generation, natural language processing, ... -
Automatic Extraction of Biometric Descriptors Based on Gait
(UMA Editorial, 2023)Nowadays, people identification is a topic of interest due to its implications in terms of safety, service automation and sanitary control. Historically, people have been identified by using its face, iris, or fingerprints. ... -
CAVLCU: an efcient GPU‑based implementation of CAVLC
Fuentes-Alventosa, Antonio; Gómez-Luna, Juan; González-Linares, José María; Guil-Mata, Nicolás; Medina-Carnicer, Rafael (Springer Nature, 2022)
In this paper, we present CAVLCU, an efficient implementation of CAVLC on GPU, which is based on four key ideas. First, we use only one kernel to avoid the long latency global memory accesses required to transmit intermediate ... -
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 ... -
Deep multi-task learning for gait-based biometrics.
Marín Jiménez, Manuel Jesús; Castro, Francisco M.; Guil-Mata, Nicolás; de la Torre, Fernando; Medina-Carnicer, Rafael (IEEE, 2017)
The task of identifying people by the way they walk is known as `gait recognition'. Although gait is mainly used for identification, additional tasks as gender recognition or age estimation may be addressed based on gait ... -
Deep Neural Network to Remove Motion Artifacts from Heart Rate Sensor Embedded on Handle Cane.
Villalba-Bravo, Rafael; Ruiz Barroso, Paula; Castro, Francisco M.; Trujillo-León, Andrés; Guil-Mata, Nicolás; Vidal-Verdú, Fernando[et al.] (IEEE, 2024)
Devices worn on the body that track physiological metrics, such as heart rate (HR) and skin conductance, have gained popularity and are typically found in items like smart-watches and bracelets. However, these measurements ... -
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 ... -
Empirical study of human pose representations for gait recognition
Cubero Torres, Nicolás; Castro, Francisco M.; Ramos-Cózar, Julián; Guil-Mata, Nicolás; Marín-Jiménez, Manuel José (Elsevier, 2025-02-28)
Gait recognition has gained attention for its ability to identify individuals from afar. Current state-of-the-art approaches predominantly utilize visual information, such as silhouettes, or a combination of visual data ... -
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 ... -
Energy-based tuning of convolution neural networks on multi-GPUs
Castro Payán, Francisco Manuel; Guil-Mata, Nicolás; Marín Jiménez, Manuel Jesús; Pérez-Serrano, Jesús; Ujaldon-Martínez, Manuel (Wiley, 2019-11)
Deep Learning (DL) applications are gaining momentum in the realm of Artificial Intelligence, particularly after GPUs have demonstrated remarkable skills for accelerating their challenging computational requirements. Within ... -
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 ... -
FADE: Forecasting for anomaly detection on ECG
Ruiz Barroso, Paula; Castro, Francisco M.; Miranda-Calero, José Ángel; Constantinescu, Denisa-Andreea; Atienza, David A.; Guil-Mata, Nicolás[et al.] (Elsevier, 2025-04-22)
Background and Objective: Cardiovascular diseases, a leading cause of noncommunicable disease-related deaths, require early and accurate detection to improve patient outcomes. Taking advantage of advances in machine learning ... -
Fisher Motion Descriptor for Multiview Gait Recognition.
Castro, Francisco M.; Marín Jiménez, Manuel Jesús; Guil-Mata, Nicolás; Muñoz-Salinas, Rafael (World Scientific, 2017)
This paper aims to identify individuals by analyzing their gait using motion descriptors based on densely sampled short-term trajectories, instead of traditional binary silhouettes. The approach leverages advanced people ... -
FlexSched: Efficient scheduling techniques for concurrent kernel execution on GPUs
López Albelda, Bernabé; Castro, Francisco M.; González-Linares, José María; Guil-Mata, Nicolás (Springer Nature, 2022)
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. In this ... -
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 ...