Sparse Representations and Efficient Sensing of Data
نویسندگان
چکیده
This report documents the program and the outcomes of Dagstuhl Seminar 11051 “Sparse Representations and Efficient Sensing of Data”. The scope of the seminar was twofold. First, we wanted to elaborate the state of the art in the field of sparse data representation and corresponding efficient data sensing methods. Second, we planned to explore and analyze the impact of methods in computational science disciplines that serve these fields, and the possible resources allocated for industrial applications. Seminar 30. January–04. February, 2011 – www.dagstuhl.de/11051 1998 ACM Subject Classification F.2 Analysis of Algorithms and Problem Complexity, G.1 Numerical Analysis, I.4 Image Processing and Computer Vision, J.2 Physical Sciences and Engineering
منابع مشابه
Image Classification via Sparse Representation and Subspace Alignment
Image representation is a crucial problem in image processing where there exist many low-level representations of image, i.e., SIFT, HOG and so on. But there is a missing link across low-level and high-level semantic representations. In fact, traditional machine learning approaches, e.g., non-negative matrix factorization, sparse representation and principle component analysis are employed to d...
متن کاملBlock-Based Compressive Sensing Using Soft Thresholding of Adaptive Transform Coefficients
Compressive sampling (CS) is a new technique for simultaneous sampling and compression of signals in which the sampling rate can be very small under certain conditions. Due to the limited number of samples, image reconstruction based on CS samples is a challenging task. Most of the existing CS image reconstruction methods have a high computational complexity as they are applied on the entire im...
متن کاملModeling the potential of Sand and Dust Storm sources formation using time series of remote sensing data, fuzzy logic and artificial neural network (A Case study of Euphrates basin)
Due to the differences between the visible and thermal infrared images, the combination of these two types of images leads to better understanding of the characteristics of targets and the environment. Thermal infrared images are really in distinguishing targets from the background based on the radiation differences and land surface temperature (LST) calculation. However, their spatial resolu...
متن کاملAccelerating Magnetic Resonance Imaging through Compressed Sensing Theory in the Direction space-k
Magnetic Resonance Imaging (MRI) is a noninvasive imaging method widely used in medical diagnosis. Data in MRI are obtained line-by-line within the K-space, where there are usually a great number of such lines. For this reason, magnetic resonance imaging is slow. MRI can be accelerated through several methods such as parallel imaging and compressed sensing, where a fraction of the K-space lines...
متن کاملA Total Ratio of Vegetation Index (TRVI) for Shrubs Sparse Cover Delineating in Open Woodland
Persian juniper and Pistachio are grown in low density in the rangelands of North-East of Iran. These rangelands are populated by evergreen conifers, which are widespread and present at low-density and sparse shrub of pistachio in Iran, that are not only environmentally but also genetically essential as seed sources for pistachio improvement in orchards. Rangelands offer excellent opportunities...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2011