Efficient hardware architectures for accelerating deep neural networks: Survey
In the modern-day era of technology, a paradigm shift has been witnessed in the areas
involving applications of Artificial Intelligence (AI), Machine Learning (ML), and Deep …
involving applications of Artificial Intelligence (AI), Machine Learning (ML), and Deep …
Artificial intelligence and internet of things (AI-IoT) technologies in response to COVID-19 pandemic: A systematic review
The origin of the COVID-19 pandemic has given overture to redirection, as well as
innovation to many digital technologies. Even after the progression of vaccination efforts …
innovation to many digital technologies. Even after the progression of vaccination efforts …
[HTML][HTML] Purely self-rectifying memristor-based passive crossbar array for artificial neural network accelerators
Memristor-integrated passive crossbar arrays (CAs) could potentially accelerate neural
network (NN) computations, but studies on these devices are limited to software-based …
network (NN) computations, but studies on these devices are limited to software-based …
A survey on deep learning hardware accelerators for heterogeneous hpc platforms
Recent trends in deep learning (DL) imposed hardware accelerators as the most viable
solution for several classes of high-performance computing (HPC) applications such as …
solution for several classes of high-performance computing (HPC) applications such as …
Integrated photonic tensor processing unit for a matrix multiply: a review
The explosion of artificial intelligence and machine-learning algorithms, connected to the
exponential growth of the exchanged data, is driving a search for novel application-specific …
exponential growth of the exchanged data, is driving a search for novel application-specific …
A collective AI via lifelong learning and sharing at the edge
A Soltoggio, E Ben-Iwhiwhu, V Braverman… - Nature Machine …, 2024 - nature.com
One vision of a future artificial intelligence (AI) is where many separate units can learn
independently over a lifetime and share their knowledge with each other. The synergy …
independently over a lifetime and share their knowledge with each other. The synergy …
Merrc: A memristor-enabled reconfigurable low-power reservoir computing architecture at the edge
The massive growth in the Internet of Things (IoT) has led to an increase in demand for
devices receiving and transmitting data to and from the cloud during operations. Edge …
devices receiving and transmitting data to and from the cloud during operations. Edge …
Energy-latency attacks via sponge poisoning
Sponge examples are test-time inputs carefully optimized to increase energy consumption
and latency of neural networks when deployed on hardware accelerators. In this work, we …
and latency of neural networks when deployed on hardware accelerators. In this work, we …
[HTML][HTML] Practical ANN prediction models for the axial capacity of square CFST columns
F Đorđević, SM Kostić - Journal of Big Data, 2023 - Springer
In this study, two machine-learning algorithms based on the artificial neural network (ANN)
model are proposed to estimate the ultimate compressive strength of square concrete-filled …
model are proposed to estimate the ultimate compressive strength of square concrete-filled …
[HTML][HTML] In-vehicle network intrusion detection systems: a systematic survey of deep learning-based approaches
F Luo, J Wang, X Zhang, Y Jiang, Z Li, C Luo - PeerJ Computer Science, 2023 - peerj.com
Developments in connected and autonomous vehicle technologies provide drivers with
many convenience and safety benefits. Unfortunately, as connectivity and complexity within …
many convenience and safety benefits. Unfortunately, as connectivity and complexity within …