Search Results - "Laroche, Clément"

Pesticide concentration monitoring: Investigating spatio‐temporal patterns in left censored data by Laroche, Clément, Olteanu, Madalina, Rossi, Fabrice

“…Monitoring pesticide concentration is very important for public authorities given the major concerns for environmental safety and the likelihood for increased…”
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Comparing neural network architectures for non-intrusive speech quality prediction by Schill, Leif Førland, Piechowiak, Tobias, Laroche, Clément, Mowlaee, Pejman

“…Non-intrusive speech quality predictors evaluate speech quality without the use of a reference signal, making them useful in many practical applications…”
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Implicitizing rational curves by the method of moving quadrics by Busé, Laurent, Laroche, Clément, Yıldırım, Fatmanur

“…A new technique for finding implicit matrix-based representations of rational curves in arbitrary dimension is introduced. It relies on the use of moving…”
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Implicit representations of high-codimension varieties by Emiris, Ioannis Z., Konaxis, Christos, Laroche, Clément

“…Implicitization usually focuses on plane curves and (hyper)surfaces, in other words, varieties of codimension 1. In this paper we shift the focus on space…”
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Hybrid Projective Nonnegative Matrix Factorization With Drum Dictionaries for Harmonic/Percussive Source Separation by Laroche, Clement, Kowalski, Matthieu, Papadopoulos, Helene, Richard, Gael

“…One of the most general models of music signals considers that such signals can be represented as a sum of two distinct components: a tonal part that is sparse…”
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Drum extraction in single channel audio signals using multi-layer Non negative Matrix Factor Deconvolution by Laroche, Clement, Papadopoulos, Helene, Kowalski, Matthieu, Richard, Gael

“…In this paper, we propose a supervised multilayer factorization method designed for harmonic/percussive source separation and drum extraction. Our method…”
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An Implicit Representation of Swept Volumes based on Local Shapes and Movements by Laroche, Clément

“…We introduce a new way to implicitly represent swept volumes in 3D. We first implicitize the base volume and then apply the time-dependent rigid transformation…”
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Extending a Morse function to a non-orientable $3-$manifold by Laroche, Clément

“…Considering a solid 3-dimensional Klein bottle and a collaring of its boundary, can we extend a generic $C^\infty$ non-singular function defined on the…”
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Pesticide concentration monitoring: investigating spatio-temporal patterns in left censored data by Laroche, Clément, Olteanu, Madalina, Rossi, Fabrice

“…Monitoring pesticide concentration is very important for public authorities given the major concerns for environmental safety and the likelihood for increased…”
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Resource-Efficient Speech Quality Prediction through Quantization Aware Training and Binary Activation Maps by Nilsson, Mattias, Miccini, Riccardo, Laroche, Clément, Piechowiak, Tobias, Zenke, Friedemann

“…Proceedings of Interspeech 2024 As speech processing systems in mobile and edge devices become more commonplace, the demand for unintrusive speech quality…”
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Towards a tailored mixed-precision sub-8-bit quantization scheme for Gated Recurrent Units using Genetic Algorithms by Miccini, Riccardo, Cerioli, Alessandro, Laroche, Clément, Piechowiak, Tobias, Sparsø, Jens, Pezzarossa, Luca

“…Despite the recent advances in model compression techniques for deep neural networks, deploying such models on ultra-low-power embedded devices still proves…”
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On Crowdsourcing-design with Comparison Category Rating for Evaluating Speech Enhancement Algorithms by Suárez, Angélica S. Z, Laroche, Clément, Clemmensen, Line H, Das, Sneha

“…Speech enhancement techniques improve the quality or the intelligibility of an audio signal by removing unwanted noise. It is used as preprocessing in numerous…”
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Dynamic nsNet2: Efficient Deep Noise Suppression with Early Exiting by Miccini, Riccardo, Zniber, Alaa, Laroche, Clément, Piechowiak, Tobias, Schoeberl, Martin, Pezzarossa, Luca, Karrakchou, Ouassim, Sparsø, Jens, Ghogho, Mounir

“…Although deep learning has made strides in the field of deep noise suppression, leveraging deep architectures on resource-constrained devices still proved…”
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On Crowdsourcing-Design with Comparison Category Rating for Evaluating Speech Enhancement Algorithms by Suarez, Angelica S. Z., Laroche, Clement, Clemmensen, Line H., Das, Sneha

“…Speech enhancement techniques improve the quality or the intelligibility of an audio signal by removing unwanted noise. It is used as preprocessing in numerous…”
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NeuralCasting: A Front-End Compilation Infrastructure for Neural Networks by Cerioli, Alessandro, Miccini, Riccardo, Laroche, Clement, Piechowiak, Tobias, Pezzarossa, Luca, Sparso, Jens, Schoeberl, Martin

“…This study presents the development of NeuralCasting, a front-end compiler framework capable of converting (casting) neural networks encoded in the ONNX format…”
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Dynamic nsNET2: Efficient Deep Noise Suppression with Early Exiting by Miccini, Riccardo, Zniber, Alaa, Laroche, Clement, Piechowiak, Tobias, Schoeberl, Martin, Pezzarossa, Luca, Karrakchou, Ouassim, Sparso, Jens, Ghogho, Mounir

“…Although deep learning has made strides in the field of deep noise suppression, leveraging deep architectures on resourceconstrained devices still proved…”
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Demystifying Orthogonal Monte Carlo and Beyond by Lin, Han, Chen, Haoxian, Zhang, Tianyi, Laroche, Clement, Choromanski, Krzysztof

“…Orthogonal Monte Carlo (OMC) is a very effective sampling algorithm imposing structural geometric conditions (orthogonality) on samples for variance reduction…”
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A structured nonnegative matrix factorization for source separation by Laroche, Clement, Kowalski, Matthieu, Papadopoulos, Helene, Richard, Gael

“…In this paper, we propose a new unconstrained nonnegative matrix factorization method designed to utilize the multilayer structure of audio signals to improve…”
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Matrix representations by means of interpolation by Emiris, Ioannis Z, Konaxis, Christos, Kotsireas, Ilias S, Laroche, Clement

“…We examine implicit representations of parametric or point cloud models, based on interpolation matrices, which are not sensitive to base points. We show how…”
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