Zobrazeno 1 - 10
of 94
pro vyhledávání: '"AI hardware"'
Autor:
Lorenzo Diana, Pierpaolo Dini
Publikováno v:
Remote Sensing, Vol 16, Iss 21, p 3957 (2024)
Neural networks (NNs) have proven their ability to deal with many computer vision tasks, including image-based remote sensing such as the identification and segmentation of hyperspectral images captured by satellites. Often, NNs run on a ground syste
Externí odkaz:
https://doaj.org/article/16888d5005a741acb3ad7776fd04ac6d
Autor:
Speiser, Michel
Artificial Intelligence and Systems of the Earth is a book about the potential and capabilities of artificial intelligence (AI) and machine learning (ML) for studying the Earth. It aims to serve as an eye-opener on new avenues of scientific research
Externí odkaz:
https://library.oapen.org/handle/20.500.12657/94031
Publikováno v:
Neuromorphic Computing and Engineering, Vol 4, Iss 4, p 044005 (2024)
Designing algorithms for versatile AI hardware that can learn on the edge using both labeled and unlabeled data is challenging. Deep end-to-end training methods incorporating phases of self-supervised and supervised learning are accurate and adaptabl
Externí odkaz:
https://doaj.org/article/04ec57df299f472d84e7fde898da8da5
Autor:
Andrew Chamberlin, Andrew Gerber, Mason Palmer, Tim Goodale, Noel Daniel Gundi, Koushik Chakraborty, Sanghamitra Roy
Publikováno v:
Journal of Low Power Electronics and Applications, Vol 14, Iss 1, p 4 (2024)
Artificial Intelligence (AI) hardware accelerators have seen tremendous developments in recent years due to the rapid growth of AI in multiple fields. Many such accelerators comprise a Systolic Multiply–Accumulate Array (SMA) as its computational b
Externí odkaz:
https://doaj.org/article/459c4dfd9fb149b5ad98690e9a77cb02
Akademický článek
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Akademický článek
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Publikováno v:
Frontiers in Physics, Vol 10 (2022)
We present a case for low batch-size inference with the potential for adaptive training of a lean encoder model. We do so in the context of a paradigmatic example of machine learning as applied in data acquisition at high data velocity scientific use
Externí odkaz:
https://doaj.org/article/d38a53d3cad845f4a80809a07363ae4e
Publikováno v:
Frontiers in Physics, Vol 10 (2022)
The emergence of novel computational hardware is enabling a new paradigm for rapid machine learning model training. For the Department of Energy’s major research facilities, this developing technology will enable a highly adaptive approach to exper
Externí odkaz:
https://doaj.org/article/7024d4a18bd841bdb893a637f1dc3c38
Publikováno v:
Information, Vol 14, Iss 9, p 516 (2023)
Universal adversarial perturbations are image-agnostic and model-independent noise that, when added to any image, can mislead the trained deep convolutional neural networks into the wrong prediction. Since these universal adversarial perturbations ca
Externí odkaz:
https://doaj.org/article/62973fb52f7d4e2cbcaf3b9664481488
Publikováno v:
Applied Sciences, Vol 13, Iss 15, p 9017 (2023)
The automation of railroad operations is a rapidly growing industry. In 2023, a new European standard for the automated Grade of Automation (GoA) 2 over European Train Control System (ETCS) driving is anticipated. Meanwhile, railway stakeholders are
Externí odkaz:
https://doaj.org/article/72140c9c3e4f427096ce38b2afa531d4