A comprehensive survey on model compression and acceleration
T Choudhary, V Mishra, A Goswami… - Artificial Intelligence …, 2020 - Springer
In recent years, machine learning (ML) and deep learning (DL) have shown remarkable
improvement in computer vision, natural language processing, stock prediction, forecasting …
improvement in computer vision, natural language processing, stock prediction, forecasting …
From cloud down to things: An overview of machine learning in internet of things
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 …
meet the requirement of all IoT applications. The limited computation and communication …
CorNET: Deep learning framework for PPG-based heart rate estimation and biometric identification in ambulant environment
Advancements in wireless sensor network technologies have enabled the proliferation of
miniaturized body-worn sensors, capable of long-term pervasive biomedical signal …
miniaturized body-worn sensors, capable of long-term pervasive biomedical signal …
Autonomous, onboard vision-based trash and litter detection in low altitude aerial images collected by an unmanned aerial vehicle
Public littering and discarded trash are, despite the effort being put to limit it, still a serious
ecological, aesthetic, and social problem. The problematic waste is usually localised and …
ecological, aesthetic, and social problem. The problematic waste is usually localised and …
On-device deep learning for mobile and wearable sensing applications: A review
OD Incel, SÖ Bursa - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
Although running deep-learning (DL) algorithms is challenging due to resource constraints
on mobile and wearable devices, they provide performance improvements compared to …
on mobile and wearable devices, they provide performance improvements compared to …
Diana: An end-to-end hybrid digital and analog neural network soc for the edge
DIgital-ANAlog (DIANA), a heterogeneous multi-core accelerator, combines a reduced
instruction set computer-five (RISC-V) host processor with an analog in-memory computing …
instruction set computer-five (RISC-V) host processor with an analog in-memory computing …
Machine learning in resource-scarce embedded systems, FPGAs, and end-devices: A survey
The number of devices connected to the Internet is increasing, exchanging large amounts of
data, and turning the Internet into the 21st-century silk road for data. This road has taken …
data, and turning the Internet into the 21st-century silk road for data. This road has taken …
Toward intelligent industrial informatics: A review of current developments and future directions of artificial intelligence in industrial applications
Research, the universal pursuit of new knowledge, is embarking on a fresh journey into
artificial intelligence (AI). ature reports that AI arose nine places to the fourth-most popular …
artificial intelligence (AI). ature reports that AI arose nine places to the fourth-most popular …
Integration of 5G and Block‐Chain Technologies in Smart Telemedicine Using IoT
The Internet of Health Thing (IoHT) has various applications in healthcare. Modern
IoHTintegrates health‐related things like sensors and remotely observed medical devices …
IoHTintegrates health‐related things like sensors and remotely observed medical devices …
The deep learning solutions on lossless compression methods for alleviating data load on IoT nodes in smart cities
Networking is crucial for smart city projects nowadays, as it offers an environment where
people and things are connected. This paper presents a chronology of factors on the …
people and things are connected. This paper presents a chronology of factors on the …