Audio-Visual Object Extraction using Graph Cuts

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The effective representation, processing, analysis, and visualization of large-scale structured data, especially those related to complex domains, such as networks and graphs, are one of the key questions in modern machine learning. Graph signal processing ...

Thanks to recent advances in signal processing, the interest for fast ℓ1-regularized reconstruction algorithms in cryo-electron microscopy (cryo-EM) has intensified. The approaches based on the alternating-direction of multipliers method (ADMM) are particu ...

Introduction The Gamma Knife(R)planning software (TMR 10, Elekta Instruments, AB, Sweden) affords two ways of defining the skull volume, the "historical" one using manual measurements (still perform in some centers) and the new one using image-based skull ...

Though deep learning (DL) algorithms are very powerful for image processing tasks, they generally require a lot of data to reach their full potential. Furthermore, there is no straightforward way to impose various properties, given by the prior knowledge a ...

The spatial and formal conception of architecture, and thus its modes of design perception and representation, directly contributes to its machine-learnability; and consequently, its capacity in leveraging today's machine learning apparatus for design inno ...

As of today, the extension of the human visual capabilities to machines remains both a cornerstone and an open challenge in the attempt to develop intelligent systems. On the one hand, the development of more and more sophisticated imaging devices, capable ...

A computer-implemented method for operating a haptic device, the haptic device comprising a plurality of tactile displays configured to provide haptic stimuli to a user, the method including the steps of (a) processing an audio signal derived from an audio ...

Most state-of-the-art approaches to road extraction from aerial images rely on a CNN trained to label road pixels as foreground and remainder of the image as background. The CNN is usually trained by minimizing pixel-wise losses, which is less than ideal t ...

Learning set functions is a key challenge arising in many domains, ranging from sketching graphs to black-box optimization with discrete parameters. In this paper we consider the problem of efficiently learning set functions that are defined over a ground ...

In this paper we present Aligned Scores and Performances (ASAP): a new dataset of 222 digital musical scores aligned with 1068 performances (more than 92 hours) of Western classical piano music.The scores are provided as paired MusicXML files and quantized ...

Audio-Visual Object Extraction using Graph Cuts

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ASAP: a Dataset of Aligned Scores and Performances for Piano Transcription