El fabricante chino de electrónica crea un aparato capaz de volar 27 minutos mientras graba en calidad 4K o hace fotos de 16 megapíxeles.
Lea la noticia entera en [http://tecnologia.elpais.com/tecnologia/2016/05/25/actualidad/1464188379_614912.html]
Título del artículo: "An extended Volumegrams of Local Binary sub-Patterns Descriptor for Hand-Gesture Recognition"
Autores: Ana I Maqueda, Carlos R. del-Blanco, Fernando Jaureguizar, Narciso García
Paper title: "Improved 2D-to-3D video conversion by fusing optical flow analysis and scene depth learning"
Authors: J.L. Herrera, C.R. delBlanco, N. García
Paper title: "Fast Image Decoding for Block Compressed Sensing based encoding by using a Modified Smooth L0-norm"
Authors: J. Xiao, C.R. delBlanco, C. Cuevas, N. García.
Welcome to MSTC
ETSIT – Telecommunication Engineering School – at Universidad Politécnica de Madrid (UPM) currently offers an Official Master Program in Signal Theory and Communications (MSTC).
Students can choose between three tracks to meet their academic needs and achieve their personal and professional objectives. The first two tracks offer advanced training in Radiofrequency and Radiocomunications and Multimedia where the Signals, Systems and Radiocommunications Department at ETSIT-UPM has a unique expertise. The third track offers a cutting-edge program in Signal Processing and Machine Learning for Big Data designed to address the increasing demand for professionals and researchers with the right skills to extend Big Data and Analytics paradigms to applications that scale to massive signals and multimedia data.
RF Technologies and Systems
Learn about the last advances in radiofrequency technologies and their application to communication systems. You will be able to design such communication subsystems as transmitters, receivers, synthesyzers and antennas.
Radiocommunications and multimedia
This track provides an integrated profile in radiocommunications and multimedia emphasizing most hot technological areas where our department is leading industrial transfer and basic research.
Signal Processing and Machine Learning for Big Data
The track program has been designed to provide the scientific foundations and major technological challenges for extracting knowledge from the increasing number of real-world signals, such as speech, images, movies, music, biological and sensor readings, financial series, etc., as well as data provided by current and future communication systems.
|More information||Pre-register now|
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The code of the publication "Visual Face Recognition using Bag of Dense Derivative Depth Patterns" has been realeased. This code performs face recognition using depth information. The key is the the computation of a new "bag_d3p" feature descriptor, which is delivered to a SVM for the classification task. More information in [Link].
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