Book2020, Compressive Sensing in Healthcare Mahdi Khosravy, ... Carlos A. Duque Explore book 7.1 Introduction Compressive sensing [1–5] is a new road to signal/image data sampling. It is performed using by much less required samples than one stated by the Shannon–Nyquist theorem. It depl...
1 2 - 8 2 1 2 4 7 - 9 ebook isbn: 9780128212486 9 7 8 - 0 - 1 2 - 8 2 1 2 4 8 - 6 compressive sensing in healthcare, part of the advances in ubiquitous sensing applications for healthcare series gives a review on compressive sensing techniques in a practical way, also ...
And 53% of reduction in the samples was obtained throughout the proposed system. Thus, an ensuring on-cloud healthcare clinic has been developed for healthcare industry.doi:10.1016/B978-0-12-821247-9.00013-5K. KeerthanaS. Aasha NandhiniS. RadhaCompressive Sensing in Healthcare...
This research explores the use of a technique, known as compressive sampling or compressed sensing (CS), as an efficient technique to minimise the data acquisition time for time critical microwave imaging (MWI) applications. Where a signal exhibits sparsity in the time domain, the proposed CS ...
(2020) investigates the use of CS in healthcare and considers applications, such as electrocardiogram (ECG) and electroencephalogram (EEG) sensing, that are, with the expansion of wearable computing capabilities, highly relevant for the ubicomp domain. Still, the book focuses on the sensing part ...
Based on the fact that these signals can be approximated by a linear combination of a few coefficients taken from different basis, an alternative new compression scheme based on Compressive Sensing (CS) has been proposed. CS provides a new approach concerned with signal compression and recovery by...
WG Bradley,G Bydder,WGB Jr - 《Informa Healthcare》 被引量: 48发表: 1997年 Active mode single pixel imaging in the highly turbid water environment using compressive sensing Single pixel imagingcompressive sensinggated techniquesimaging through turbid mediaUnderwater imaging has always been a challenge...
In the era of the Internet of Medical Things (IoMT), modern healthcare devices generate vast amounts of data, necessitating enhanced data processing, storage, transmission bandwidth, and increased power consumption, especially in sensing applications. Compressive Sensing (CS) addresses these challenges ...
Carlos A. Duque, in Compressive Sensing in Healthcare, 2020 11.2 Compressed sensing theory – a brief review Compressive sensing (CS) or compressive sampling is an emerging technique for acquiring and reconstructing a digital signal with potential benefits in many applications. The CS method takes ...
In this work, we investigate the problem of distributed deep learning in Internet of Things (IoT). The proposed learning framework is constructed in a fog–cloud computing architecture, so as to overcome the limitation of resource constrained IoT end device. Compressive Sensing (CS) is used as ...