Hardware approximate techniques for deep neural network accelerators: A survey

G Armeniakos, G Zervakis, D Soudris… - ACM Computing …, 2022 - dl.acm.org
Deep Neural Networks (DNNs) are very popular because of their high performance in
various cognitive tasks in Machine Learning (ML). Recent advancements in DNNs have …

I know what you trained last summer: A survey on stealing machine learning models and defences

D Oliynyk, R Mayer, A Rauber - ACM Computing Surveys, 2023 - dl.acm.org
Machine-Learning-as-a-Service (MLaaS) has become a widespread paradigm, making
even the most complex Machine Learning models available for clients via, eg, a pay-per …

Hardware and software optimizations for accelerating deep neural networks: Survey of current trends, challenges, and the road ahead

M Capra, B Bussolino, A Marchisio, G Masera… - IEEE …, 2020 - ieeexplore.ieee.org
Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning
(DL) is already present in many applications ranging from computer vision for medicine to …

An updated survey of efficient hardware architectures for accelerating deep convolutional neural networks

M Capra, B Bussolino, A Marchisio, M Shafique… - Future Internet, 2020 - mdpi.com
Deep Neural Networks (DNNs) are nowadays a common practice in most of the Artificial
Intelligence (AI) applications. Their ability to go beyond human precision has made these …

Intelligent disassembly of electric-vehicle batteries: a forward-looking overview

K Meng, G Xu, X Peng, K Youcef-Toumi, J Li - … , Conservation and Recycling, 2022 - Elsevier
Retired electric-vehicle lithium-ion battery (EV-LIB) packs pose severe environmental
hazards. Efficient recovery of these spent batteries is a significant way to achieve closed …

Towards Risk‐Free Trustworthy Artificial Intelligence: Significance and Requirements

L Alzubaidi, A Al-Sabaawi, J Bai… - … Journal of Intelligent …, 2023 - Wiley Online Library
Given the tremendous potential and influence of artificial intelligence (AI) and algorithmic
decision‐making (DM), these systems have found wide‐ranging applications across diverse …

An efficient spiking neural network for recognizing gestures with a dvs camera on the loihi neuromorphic processor

R Massa, A Marchisio, M Martina… - 2020 International Joint …, 2020 - ieeexplore.ieee.org
Spiking Neural Networks (SNNs), the third generation NNs, have come under the spotlight
for machine learning based applications due to their biological plausibility and reduced …

Machine learning on the COVID-19 pandemic, human mobility and air quality: A review

MM Rahman, KC Paul, MA Hossain, GGMN Ali… - Ieee …, 2021 - ieeexplore.ieee.org
The ongoing COVID-19 global pandemic is touching every facet of human lives (eg, public
health, education, economy, transportation, and the environment). This novel pandemic and …

A survey of trustworthy federated learning with perspectives on security, robustness and privacy

Y Zhang, D Zeng, J Luo, Z Xu, I King - … of the ACM Web Conference 2023, 2023 - dl.acm.org
Trustworthy artificial intelligence (AI) technology has revolutionized daily life and greatly
benefited human society. Among various AI technologies, Federated Learning (FL) stands …

A systematic literature review on hardware reliability assessment methods for deep neural networks

MH Ahmadilivani, M Taheri, J Raik… - ACM Computing …, 2024 - dl.acm.org
Artificial Intelligence (AI) and, in particular, Machine Learning (ML), have emerged to be
utilized in various applications due to their capability to learn how to solve complex …