Search results for "Sound"

Improved Statistically Based Retrievals via Spatial-Spectral Data Compression for IASI Data

2019

In this paper, we analyze the effect of spatial and spectral compression on the performance of statistically based retrieval. Although the quality of the information is not com- pletely preserved during the coding process, experiments reveal that a certain amount of compression may yield a positive impact on the accuracy of retrievals. We unveil two strategies, both with interesting benefits: either to apply a very high compression, which still maintains the same retrieval performance as that obtained for uncompressed data; or to apply a moderate to high compression, which improves the performance. As a second contribution of this paper, we focus on the origins of these benefits. On the one…

Matlab-based interface for the simultaneous acquisition of force measures and Doppler ultrasound muscular images

2012

This paper tackles the design of a graphical user interface (GUI) based on Matlab (MathWorks Inc., MA), a worldwide standard in the processing of biosignals, which allows the acquisition of muscular force signals and images from a ultrasound scanner simultaneously. Thus, it is possible to unify two key magnitudes for analyzing the evolution of muscular injuries: the force exerted by the muscle and section/length of the muscle when such force is exerted. This paper describes the modules developed to finally show its applicability with a case study to analyze the functioning capacity of the shoulder rotator cuff.

Robust Resolution-Enhanced Prostate Segmentation in Magnetic Resonance and Ultrasound Images through Convolutional Neural Networks

2021

[EN] Prostate segmentations are required for an ever-increasing number of medical applications, such as image-based lesion detection, fusion-guided biopsy and focal therapies. However, obtaining accurate segmentations is laborious, requires expertise and, even then, the inter-observer variability remains high. In this paper, a robust, accurate and generalizable model for Magnetic Resonance (MR) and three-dimensional (3D) Ultrasound (US) prostate image segmentation is proposed. It uses a densenet-resnet-based Convolutional Neural Network (CNN) combined with techniques such as deep supervision, checkpoint ensembling and Neural Resolution Enhancement. The MR prostate segmentation model was tra…

RF-Based Human Activity Recognition: A Non-stationary Channel Model Incorporating the Impact of Phase Distortions

2019

This paper proposes a non-stationary channel model that captures the impact of the time-variant (TV) phase distortion caused by hardware imperfections. The model allows for studying the spectrogram of in-home radio channels influenced by walking activities of the home user under realistic non-stationary propagation conditions. The resolution of the spectrogram is investigated for the von-Mises distribution of the phase distortion. It is shown that high-entropy distributions considerably mask fingerprints of the user activity on the spectrogram of the channel. For an orthogonal frequency-division multiplexing (OFDM) system, a computationally simple method for mitigating the undesired phase r…

Design and evaluation of prosody-based non-speech audio feedback for physical training application

2011

Abstract Methodological support for the design of non-speech user interface sounds for human–computer interaction is still fairly scarce. To meet this challenge, this paper presents a sound design case which, as a practical design solution for a wrist-computer physical training application, outlines a prosody-based method for designing non-speech user interface sounds. The principles used in the design are based on nonverbal communicative functions of prosody in speech acts, exemplifying an interpersonal approach to sonic interaction design. The stages of the design process are justified with a theoretical analysis and three empirical sub-studies, which comprise production and recognition t…

Spectrogram analysis of multipath fading channels

2015

The analysis of the Doppler power spectral density (PSD) of measured and simulated data is an important topic in the area of mobile radio channel modelling. In this paper, we estimate the Doppler PSD of multipath fading channels by using the concept of the spectrogram. The spectrogram is a spectral representation that gives insight into how the distribution of the spectral density of a signal changes over time. The multipath fading channel is modelled by a sum-of-cisoids (SOC) process. A closed-form solution is presented for the spectrogram and the corresponding time-dependent autocorrelation function (ACF). The closed-form solutions disclose several unwanted effects that come with the limi…

A Musical Pattern Discovery System Founded on a Modeling of Listening Strategies

2004

Music is a domain of expression that conveys a paramount degree of complexity. The musical surface, composed of a multitude of notes, results from the elaboration of numerous structures of different types and sizes. The composer constructs this structural complexity in a more or less explicit way. The listener, faced by such a complex phenomenon, is able to reconstruct only a limited part of it, mostly in a non-explicit way. One particular aim of music analysis is to objectify such complexity, thus offering to the listener a tool for enriching the appreciation of music (Lartillot and SaintJames, 2004). The trouble is, traditional musical analysis, although offering a valuable understanding …

Non-speech voice for sonic interaction: a catalogue

2016

This paper surveys the uses of non-speech voice as an interaction modality within sonic applications. Three main contexts of use have been identified: sound retrieval, sound synthesis and control, and sound design. An overview of different choices and techniques regarding the style of interaction, the selection of vocal features and their mapping to sound features or controls is here displayed. A comprehensive collection of examples instantiates the use of non-speech voice in actual tools for sonic interaction. It is pointed out that while voice-based techniques are already being used proficiently in sound retrieval and sound synthesis, their use in sound design is still at an exploratory p…

2020

Abstract Background and objective Deep learning approaches are common in image processing, but often rely on supervised learning, which requires a large volume of training images, usually accompanied by hand-crafted labels. As labelled data are often not available, it would be desirable to develop methods that allow such data to be compiled automatically. In this study, we used a Generative Adversarial Network (GAN) to generate realistic B-mode musculoskeletal ultrasound images, and tested the suitability of two automated labelling approaches. Methods We used a model including two GANs each trained to transfer an image from one domain to another. The two inputs were a set of 100 longitudina…

Breast Ultra-Sound image segmentation: an optimization approach based on super-pixels and high-level descriptors

2015

International audience; Breast cancer is the second most common cancer and the leading cause of cancer death among women. Medical imaging has become an indispensable tool for its diagnosis and follow up. During the last decade, the medical community has promoted to incorporate Ultra-Sound (US) screening as part of the standard routine. The main reason for using US imaging is its capability to differentiate benign from malignant masses, when compared to other imaging techniques. The increasing usage of US imaging encourages the development of Computer Aided Diagnosis (CAD) systems applied to Breast Ultra-Sound (BUS) images. However accurate delineations of the lesions and structures of the b…