TinyML for ultra-low power AI and large scale IoT deployments: A systematic review
The rapid emergence of low-power embedded devices and modern machine learning (ML)
algorithms has created a new Internet of Things (IoT) era where lightweight ML frameworks …
algorithms has created a new Internet of Things (IoT) era where lightweight ML frameworks …
TinyML: A systematic review and synthesis of existing research
Tiny Machine Learning (TinyML), a rapidly evolving edge computing concept that links
embedded systems (hardware and software) and machine learning, with the purpose of …
embedded systems (hardware and software) and machine learning, with the purpose of …
Intelligence at the extreme edge: A survey on reformable tinyml
Machine Learning (TinyML) is an upsurging research field that proposes to democratize the
use of Machine Learning and Deep Learning on highly energy-efficient frugal …
use of Machine Learning and Deep Learning on highly energy-efficient frugal …
Widening access to applied machine learning with tinyml
VJ Reddi, B Plancher, S Kennedy, L Moroney… - arXiv preprint arXiv …, 2021 - arxiv.org
Broadening access to both computational and educational resources is critical to diffusing
machine-learning (ML) innovation. However, today, most ML resources and experts are …
machine-learning (ML) innovation. However, today, most ML resources and experts are …
[HTML][HTML] Towards secure private and trustworthy human-centric embedded machine learning: An emotion-aware facial recognition case study
The use of artificial intelligence (AI) at the edge is transforming every aspect of the lives of
human beings from scheduling daily activities to personalized shopping recommendations …
human beings from scheduling daily activities to personalized shopping recommendations …
A review of on-device machine learning for IoT: An energy perspective
Recently, there has been a substantial interest in on-device Machine Learning (ML) models
to provide intelligence for the Internet of Things (IoT) applications such as image …
to provide intelligence for the Internet of Things (IoT) applications such as image …
A gas leakage detection device based on the technology of TinyML
Internet of Things devices are frequently used as consumer devices to provide digital
solutions, such as smart lighting and digital voice-activated assistants, but they are also …
solutions, such as smart lighting and digital voice-activated assistants, but they are also …
Security and privacy of blockchain-based single-bit cache memory architecture for IoT systems
This paper provides an overview of blockchain technology's security and privacy features, as
well as an overview of IoT-based cache memory and single-bit six transistor static random …
well as an overview of IoT-based cache memory and single-bit six transistor static random …
Efficient people counting in thermal images: the benchmark of resource-constrained hardware
The monitoring of presence is a timely topic in intelligent building management systems.
Nowadays, most rooms, halls, and auditoriums use a simple binary presence detector that is …
Nowadays, most rooms, halls, and auditoriums use a simple binary presence detector that is …
On-device Online Learning and Semantic Management of TinyML Systems
Recent advances in Tiny Machine Learning (TinyML) empower low-footprint embedded
devices for real-time on-device Machine Learning (ML). While many acknowledge the …
devices for real-time on-device Machine Learning (ML). While many acknowledge the …