Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Bossmann, Florian"'
Deep learning techniques have shown significant potential in many applications through recent years. The achieved results often outperform traditional techniques. However, the quality of a neural network highly depends on the used training data. Nois
Externí odkaz:
http://arxiv.org/abs/2404.16324
Identifying objects in given data is a task frequently encountered in many applications. Finding vehicles or persons in video data, tracking seismic waves in geophysical exploration data, or predicting a storm front movement from meteorological measu
Externí odkaz:
http://arxiv.org/abs/2402.02395
Autor:
Bossmann, Florian, Wu, Wenze
Object recognition and reconstruction is of great interest in many research fields. Detecting pedestrians or cars in traffic cameras or tracking seismic waves in geophysical exploration are only two of many applications. Recently, the authors develop
Externí odkaz:
http://arxiv.org/abs/2211.09362
Autor:
Bossmann, Florian, Ma, Jianwei
Publikováno v:
Inverse Problems 38 125009, 2022
Data processing has to deal with many practical difficulties. Data is often corrupted by artifacts or noise and acquiring data can be expensive and difficult. Thus, the given data is often incomplete and inaccurate. To overcome these problems, it is
Externí odkaz:
http://arxiv.org/abs/2206.00365
We propose a novel sparsity model for distributed compressed sensing in the multiple measurement vectors (MMV) setting. Our model extends the concept of row-sparsity to allow more general types of structured sparsity arising in a variety of applicati
Externí odkaz:
http://arxiv.org/abs/2103.01908
Akademický článek
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Autor:
Sissouno, Nada, Boßmann, Florian, Filbir, Frank, Iwen, Mark, Kahnt, Maik, Saab, Rayan, Schroer, Christian, Castell, Wolfgang zu
Measurements achieved with ptychographic imaging are a special case of diffraction measurements. They are generated by illuminating small parts of a sample with, e.g., a focused X-ray beam. By shifting the sample, a set of far-field diffraction patte
Externí odkaz:
http://arxiv.org/abs/1904.07940
Autor:
Boßmann, Florian, Ma, Jianwei
Low rank approximation has been extensively studied in the past. It is most suitable to reproduce rectangular like structures in the data. In this work we introduce a generalization using shifted rank-1 matrices to approximate $A\in\mathbb{C}^{M\time
Externí odkaz:
http://arxiv.org/abs/1810.01681
Mathematical methods of image inpainting involve the discretization of given continuous models. We present a method that avoids the standard pointwise discretization by modeling known variational approaches, in particular total variation (TV), using
Externí odkaz:
http://arxiv.org/abs/1705.08303
Autor:
Boßmann, Florian
Sparse data approximation has become a popular research topic in signal processing. However, in most cases only a single measurement vector (SMV) is considered. In applications, the multiple measurement vector (MMV) case is more usual, i.e., the spar
Externí odkaz:
http://arxiv.org/abs/1705.08259