F Samie, L Bauer, J Henkel - IEEE Internet of Things Journal, 2019 - ieeexplore.ieee.org
With the numerous Internet of Things (IoT) devices, the cloud-centric data processing fails to meet the requirement of all IoT applications. The limited computation and communication …
Abstract Machine learning has recently emerged as a powerful technique to increase operational efficiency or to develop new value propositions. However, the translation of a …
JF Miller - Genetic Programming and Evolvable Machines, 2020 - Springer
Cartesian genetic programming, a well-established method of genetic programming, is approximately 20 years old. It represents solutions to computational problems as graphs. Its …
C Vidal, O Gross, R Gu, P Kollmeyer… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
The purpose of this paper is to review the recent literature regarding the effects of low temperatures on Lithium ion (Li-ion) batteries for electric vehicle, plug-in hybrid electric …
M Imani, C Huang, D Kong, T Rosing - Proceedings of the 55th Annual …, 2018 - dl.acm.org
Brain-inspired Hyperdimensional (HD) computing emulates cognition tasks by computing with hypervectors rather than traditional numerical values. In HD, an encoder maps inputs to …
Traffic Sign Detection (TSD) is a complex and fundamental task for developing autonomous vehicles; it is one of the most critical visual perception problems since failing in this task may …
J Jo, S Kim, IC Park - … Transactions on Circuits and Systems I …, 2018 - ieeexplore.ieee.org
This paper presents a rescheduled dataflow of convolution and its hardware architecture that can enhance energy efficiency. For convolution involving a large amount of …
J Zhao, M Xu, Y Chen, G Xu - Future Internet, 2023 - mdpi.com
Nowdays, DNNs (Deep Neural Networks) are widely used in the field of DDoS attack detection. However, designing a good DNN architecture relies on the designer's experience …
Y Zhao, J Yang, B Li, X Cheng, X Ye, X Wang… - Science China …, 2023 - Springer
The performance and efficiency of running large-scale datasets on traditional computing systems exhibit critical bottlenecks due to the existing “power wall” and “memory wall” …