Probabilistic Modeling Paradigms for Audio Source Separation

This is the author's final version of the article, first published as E. Vincent, M. G. Jafari, S. A. Abdallah, M. D. Plumbley, M. E. Davies. Probabilistic Modeling Paradigms for Audio Source Separation. In W. Wang (Ed), Machine Audition: Principles, Algorithms and Systems. Chapter 7, pp. 162-185. IGI Global, 2011. ISBN 978-1-61520-919-4. DOI: 10.4018/978-1-61520-919-4.ch007file: VincentJafariAbdallahPD11-probabilistic.pdf:v\VincentJafariAbdallahPD11-probabilistic.pdf:PDF owner: markp timestamp: 2011.02.04file: VincentJafariAbdallahPD11-probabilistic.pdf:v\VincentJafariAbdallahPD11-probabilistic.pdf:PDF owner: markp timestamp: 2011.02.04Most sound scenes result from the superposition of several sources, which can be separately perceived and analyzed by human listeners. Source separation aims to provide machine listeners with similar skills by extracting the sounds of individual sources from a given scene. Existing separation systems operate either by emulating the human auditory system or by inferring the parameters of probabilistic sound models. In this chapter, the authors focus on the latter approach and provide a joint overview of established and recent models, including independent component analysis, local time-frequency models and spectral template-based models. They show that most models are instances of one of the following two general paradigms: linear modeling or variance modeling. They compare the merits of either paradigm and report objective performance figures. They also,conclude by discussing promising combinations of probabilistic priors and inference algorithms that could form the basis of future state-of-the-art systems

Vision-Based Road Detection in Automotive Systems: A Real-Time Expectation-Driven Approach

The main aim of this work is the development of a vision-based road detection system fast enough to cope with the difficult real-time constraints imposed by moving vehicle applications. The hardware platform, a special-purpose massively parallel system, has been chosen to minimize system production and operational costs. This paper presents a novel approach to expectation-driven low-level image segmentation, which can be mapped naturally onto mesh-connected massively parallel SIMD architectures capable of handling hierarchical data structures. The input image is assumed to contain a distorted version of a given template; a multiresolution stretching process is used to reshape the original template in accordance with the acquired image content, minimizing a potential function. The distorted template is the process output.Comment: See http://www.jair.org/ for any accompanying file

Eelgrass Distribution in the Great Bay Estuary and Piscataqua River for 2017

Eelgrass distribution in Great Bay, Little Bay, and the Piscataqua River Estuary was mapped from aerial photography acquired on August 24, 2017. The total area of eelgrass beds with 10% or greater cover and a polygon area equal to or greater than 100 square meters was 625.9 hectares or 1546.7 acres. Eelgrass polygons were coded for Assessment Zone location and the results reported for each zone. The largest concentration of eelgrass was found in Great Bay with lesser amounts in the vicinity of Portsmouth Harbor. The total area of eelgrass beds with 10% or greater cover and a polygon area equal to or greater than 100 square meters has decreased by 142 acres which is approximately an 8.5% decrease from the previous year

From ”Sapienza” to “Sapienza, State Archives in Rome”. A looping effect bringing back to the original source communication and culture by innovative and low cost 3D surveying, imaging systems and GIS applications

Applicazione di tecnologie mensorie integrate Low Cost,web GIS,applicazione di tecniche di Computational photography per la comunicazione e condivisione dei dati, sistemi di Cloud computing.Archiviazione Grandi DatiHigh Quality survey models, realized by multiple Low Cost methods and technologies, as a container to sharing Cultural and Archival Heritage, this is the aim guiding our research, here described in its primary applications. The SAPIENZA building, a XVI century masterpiece that represented the first unified headquarters of University in Rome, plays since year 1936, when the University moved to its newly edified campus, the role of the main venue for the State Archives. By the collaboration of a group of students of the Architecture Faculty, some integrated survey methods were applied on the monument with success. The beginning was the topographic survey, creating a reference on ground and along the monument for the upcoming applications, a GNNS RTK survey followed georeferencing points on the internal courtyard. Dense stereo matching photogrammetry is nowadays an accepted method for generating 3D survey models, accurate and scalable; it often substitutes 3D laser scanning for its low cost, so that it became our choice. Some 360°shots were planned for creating panoramic views of the double portico from the courtyard, plus additional single shots of some lateral spans and of pillars facing the court, as a single operation with a double finality: to create linked panotours with hotspots to web-linked databases, and 3D textured and georeferenced surface models, allowing to study the harmonic proportions of the classical architectural order. The use of free web Gis platforms, to load the work in Google Earth and the realization of low cost 3D prototypes of some representative parts, has been even performed

An integrated dexterous robotic testbed for space applications

An integrated dexterous robotic system was developed as a testbed to evaluate various robotics technologies for advanced space applications. The system configuration consisted of a Utah/MIT Dexterous Hand, a PUMA 562 arm, a stereo vision system, and a multiprocessing computer control system. In addition to these major subsystems, a proximity sensing system was integrated with the Utah/MIT Hand to provide capability for non-contact sensing of a nearby object. A high-speed fiber-optic link was used to transmit digitized proximity sensor signals back to the multiprocessing control system. The hardware system was designed to satisfy the requirements for both teleoperated and autonomous operations. The software system was designed to exploit parallel processing capability, pursue functional modularity, incorporate artificial intelligence for robot control, allow high-level symbolic robot commands, maximize reusable code, minimize compilation requirements, and provide an interactive application development and debugging environment for the end users. An overview is presented of the system hardware and software configurations, and implementation is discussed of subsystem functions