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pro vyhledávání: '"Fraser, Nicholas"'
Autor:
Fraser, Nicholas Tweedie
The study takes place in the Dwarsrivier area which lies on the border between Mpumalanga and Limpopo, to the North-West of Lydenberg, at an exposed road cutting. Within the road cutting, there is a unique portion of exposed rock which is light in co
Externí odkaz:
http://hdl.handle.net/2263/76009
Publikováno v:
In Telematics and Informatics Reports June 2024 14
Publikováno v:
QSS 2023
In 2014, a union of German research organisations established Projekt DEAL, a national-level project to negotiate licensing agreements with large scientific publishers. Negotiations between DEAL and Elsevier began in 2016, and broke down without a su
Externí odkaz:
http://arxiv.org/abs/2105.12078
In recent years, increased stakeholder pressure to transition research to Open Access has led to many journals converting, or 'flipping', from a closed access (CA) to an open access (OA) publishing model. Changing the publishing model can influence t
Externí odkaz:
http://arxiv.org/abs/2103.14522
Autor:
Hawks, Benjamin, Duarte, Javier, Fraser, Nicholas J., Pappalardo, Alessandro, Tran, Nhan, Umuroglu, Yaman
Publikováno v:
Front. AI 4, 94 (2021)
Efficient machine learning implementations optimized for inference in hardware have wide-ranging benefits, depending on the application, from lower inference latency to higher data throughput and reduced energy consumption. Two popular techniques for
Externí odkaz:
http://arxiv.org/abs/2102.11289
Autor:
Petrica, Lucian, Alonso, Tobias, Kroes, Mairin, Fraser, Nicholas, Cotofana, Sorin, Blott, Michaela
Custom dataflow Convolutional Neural Network (CNN) inference accelerators on FPGA are tailored to a specific CNN topology and store parameters in On-Chip Memory (OCM), resulting in high energy efficiency and low inference latency. However, in these a
Externí odkaz:
http://arxiv.org/abs/2011.07317
Deep neural networks (DNNs) are state-of-the-art algorithms for multiple applications, spanning from image classification to speech recognition. While providing excellent accuracy, they often have enormous compute and memory requirements. As a result
Externí odkaz:
http://arxiv.org/abs/2011.05873
Deployment of deep neural networks for applications that require very high throughput or extremely low latency is a severe computational challenge, further exacerbated by inefficiencies in mapping the computation to hardware. We present a novel metho
Externí odkaz:
http://arxiv.org/abs/2004.03021
Autor:
Jiang, Da-yong, Zhou, Min, Motani, Ryosuke, Tintori, Andrea, Fraser, Nicholas C., Huang, Jian-dong, Rieppel, Olivier, Ji, Cheng, Fu, Wan-lu, Sun, Zuo-yu, Lu, Hao
Publikováno v:
In Palaeogeography, Palaeoclimatology, Palaeoecology 15 October 2023 628
In recent years, increased stakeholder pressure to transition research to Open Access has led to many journals "flipping" from a toll access to an open access publishing model. Changing the publishing model can influence the decision of authors to su
Externí odkaz:
http://arxiv.org/abs/1903.11682