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Titlebook: Design and Architectures for Signal and Image Processing; 17th International W Tiago Dias,Paola Busia Conference proceedings 2024 The Edito

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書目名稱Design and Architectures for Signal and Image Processing
副標(biāo)題17th International W
編輯Tiago Dias,Paola Busia
視頻videohttp://file.papertrans.cn/285/284571/284571.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Design and Architectures for Signal and Image Processing; 17th International W Tiago Dias,Paola Busia Conference proceedings 2024 The Edito
描述.This book constitutes the refereed proceedings of the 17th International Workshop on Design and Architecture for Signal and Image Processing, DASIP 2024, held in Munich, Germany, during January 17–19, 2024...The 9 full papers presented in this book were carefully reviewed and selected from 21 submissions.?The workshop provided an inspiring international forum for the latest innovations and developments in the fields of leading signal, image, and? video processing and machine learning in custom embedded, edge, and cloud computing architectures and systems..
出版日期Conference proceedings 2024
關(guān)鍵詞artificial intelligence; computer hardware; computer science; embedded systems; engineering; Field Progra
版次1
doihttps://doi.org/10.1007/978-3-031-62874-0
isbn_softcover978-3-031-62873-3
isbn_ebook978-3-031-62874-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Design and Architectures for Signal and Image Processing978-3-031-62874-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
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hy (PPG) is one of these trends since PPG sensors are embedded into many devices like smartwatches or oximeters. Due to the versatility of PPG, it is the technique of choice for the non-invasive monitoring of vital signs such as heart rate, respiratory rate, blood oxygen saturation and blood pressur
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ions. In particular, they have caused a large increase in memory, execution time, and power needed. One solution to address those challenges is to reduce data sizes. Custom floating-point is a good candidate that brings a large dynamic range in a compact representation. Thanks to improvement in floa
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nas drastically increases the cost of processing and storing their data, complicating the design of computing hardware. Our overall goal is to provide a system, which we term SimSDP, to aid in their design. It will achieve this by providing resource usage estimations for some given imaging pipeline
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y, selecting appropriate computing platforms for these applications is done manually through prototyping and benchmarking. To simplify this selection process, Dataflow (DF) modeling has been utilized to identify opportunities for parallelism. This approach utilizes the Algorithm Architecture “Adequa
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