Search results for "computer.software_genre"
showing 10 items of 3858 documents
Inquiry-based environments for bio-signal processing training in engineering education
2021
Active student engagement, teaching via experience in real-life settings and learning by doing, are pedagogical strategies appropriate to improve student-reasoning skills. By building models, performing investigations, examining and explaining experimental results, using theoretical and computational thinking, constructing representations, undergraduates can acquire a deeper understanding of fundamental disciplinary concepts while reinforcing transversal abilities. In this framework, Engineering courses should be designed with the final objective to develop practical skills, focusing on hands-on activities. This contribution presents two different inquiry-based learning environments recent…
Signal Processing for Image Enhancement and Multimedia Processing
2008
Proba-V cloud detection Round Robin: Validation results and recommendations
2017
This paper discusses results from 12 months of a Round Robin exercise aimed at the inter-comparison of different cloud detection algorithms for Proba-V. Clouds detection is a critical issue for satellite optical remote sensing, since potential errors in cloud masking directly translates into significant uncertainty in the retrieved downstream geophysical products. Cloud detection is particularly challenging for Proba-V due to the presence of a limited number of spectral bands and the lack of thermal infrared bands. The main objective of the project was the inter-comparison of several cloud detection algorithms for Proba-V over a wide range of surface types and environmental conditions. Prob…
On the performance of multi-GPU-based expert systems for acoustic localization involving massive microphone arrays
2015
Sound source localization is an important topic in expert systems involving microphone arrays, such as automatic camera steering systems, human-machine interaction, video gaming or audio surveillance. The Steered Response Power with Phase Transform (SRP-PHAT) algorithm is a well-known approach for sound source localization due to its robust performance in noisy and reverberant environments. This algorithm analyzes the sound power captured by an acoustic beamformer on a defined spatial grid, estimating the source location as the point that maximizes the output power. Since localization accuracy can be improved by using high-resolution spatial grids and a high number of microphones, accurate …
From Signal Processing to Machine Learning
2018
This chapter reviews the main landmarks of signal processing in the 20th century from the perspective of algorithmic developments. It focuses on cross‐fertilization with the field of statistical (machine) learning in the last decades. In the 21st century, model and data assumptions as well as algorithmic constraints are no longer valid, and the field of machine‐learning signal processing has erupted, with many successful stories to tell. The chapter also focuses on digital signal processing (DSP), which deals with the analysis of digitized and discrete sampled signals. Machine learning is a branch of computer science and artificial intelligence that enables computers to learn from data. Mac…
BioLab: An Educational Tool for Signal Processing Training in Biomedical Engineering
2007
This paper introduces and evaluates BioLab, a tool for teaching biosignal processing. BioLab has been used in the biomedical engineering module that is given in the second semester of the fifth year of the electronic engineering degree at the University of Valencia, Spain. This module and its correspondent curricular pathway are also reviewed. BioLab allows the results obtained with digital processing techniques to be shown interactively in the theory classes, and it also provides support in laboratory sessions. The graphic interface of BioLab simplifies its learning and use and provides access to processing and visualization functions by means of menus. The tool is based on Matlab since th…
Active learning in digital communications with low-cost software defined radio
2021
Las comunicaciones digitales se enseñan tradicionalmente en sesiones de laboratorio desde un punto de vista teórico, utilizando plataformas de simulación. Sin embargo, el sistema de Acreditación Académica incluye la dimensión de "lo que se espera que los estudiantes sean capaces de hacer", lo que plantea la necesidad de disminuir la brecha entre las sesiones de laboratorio simuladas y un enfoque más práctico y realista. En este trabajo, proponemos una metodología para mejorar el aprendizaje de los aspectos prácticos relacionados con los cursos de Comunicaciones Digitales, así como para aumentar la motivación de los estudiantes, mediante el uso de dispositivos de radio definida por software …
Miten viittomakielen korpusta luodaan ja mihin sitä tarvitaan? Viittomakielten korpukset ja niiden tehtävät
2020
Artikkeli käsittelee suomalaisen ja suomenruotsalaisen viittomakielen korpusten luontia CFINSL-projektissa (Corpus project of Finland’s sign languages, Suomen viittomakielten korpusprojekti). Viittomakielillä ei ole kirjoitettua muotoa, joten korpusten laatiminen vaatii erilaista lähestymistä kuin korpusten luonti sellaisille puhutuille kielille, joilla on kirjoitettu muoto. Artikkelissa kuvataan ne menetelmät, joilla Jyväskylän yliopiston viittomakielen keskuksessa on koottu aineistoa suomalaisen ja suomenruotsalaisen viittomakielen korpukseen. Lisäksi kuvataan korpusaineiston teknistä käsittelyä, annotointia, metatietojen keruuta ja käsittelyä sekä aineiston säilytystä ja tutkijoiden käyt…
An Online Metric Learning Approach through Margin Maximization
2011
This work introduces a method based on learning similarity measures between pairs of objects in any representation space that allows to develop convenient recognition algorithms. The problem is formulated through margin maximization over distance values so that it can discriminate between similar (intra-class) and dissimilar (inter-class) elements without enforcing positive definiteness of the metric matrix as in most competing approaches. A passive-aggressive approach has been adopted to carry out the corresponding optimization procedure. The proposed approach has been empirically compared to state of the art metric learning on several publicly available databases showing its potential bot…
New Similarity Rules for Mining Data
2006
Variability and noise in data-sets entries make hard the discover of important regularities among association rules in mining problems. The need exists for defining flexible and robust similarity measures between association rules. This paper introduces a new class of similarity functions, SF's, that can be used to discover properties in the feature space X and to perform their grouping with standard clustering techniques. Properties of the proposed SF's are investigated and experiments on simulated data-sets are also shown to evaluate the grouping performance.