Efficient acceleration of deep learning inference on resource-constrained edge devices: A review
Successful integration of deep neural networks (DNNs) or deep learning (DL) has resulted
in breakthroughs in many areas. However, deploying these highly accurate models for data …
in breakthroughs in many areas. However, deploying these highly accurate models for data …
An overview of machine learning within embedded and mobile devices–optimizations and applications
Embedded systems technology is undergoing a phase of transformation owing to the novel
advancements in computer architecture and the breakthroughs in machine learning …
advancements in computer architecture and the breakthroughs in machine learning …
A modified Adam algorithm for deep neural network optimization
Abstract Deep Neural Networks (DNNs) are widely regarded as the most effective learning
tool for dealing with large datasets, and they have been successfully used in thousands of …
tool for dealing with large datasets, and they have been successfully used in thousands of …
A hybrid deep learning model for brain tumour classification
A brain tumour is one of the major reasons for death in humans, and it is the tenth most
common type of tumour that affects people of all ages. However, if detected early, it is one of …
common type of tumour that affects people of all ages. However, if detected early, it is one of …
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 …
A comprehensive review of convolutional neural networks for defect detection in industrial applications
Quality inspection and defect detection remain critical challenges across diverse industrial
applications. Driven by advancements in Deep Learning, Convolutional Neural Networks …
applications. Driven by advancements in Deep Learning, Convolutional Neural Networks …
Beyond efficiency: A systematic survey of resource-efficient large language models
The burgeoning field of Large Language Models (LLMs), exemplified by sophisticated
models like OpenAI's ChatGPT, represents a significant advancement in artificial …
models like OpenAI's ChatGPT, represents a significant advancement in artificial …
Ultra-fast switching memristors based on two-dimensional materials
The ability to scale two-dimensional (2D) material thickness down to a single monolayer
presents a promising opportunity to realize high-speed energy-efficient memristors. Here …
presents a promising opportunity to realize high-speed energy-efficient memristors. Here …
A Review of Biosensors and Artificial Intelligence in Healthcare and Their Clinical Significance
In the past decade, a substantial increase in medical data from various sources, including
wearable sensors, medical imaging, personal health records, and public health …
wearable sensors, medical imaging, personal health records, and public health …
Artificial intelligence and biosensors in healthcare and its clinical relevance: A review
Data generated from sources such as wearable sensors, medical imaging, personal health
records, and public health organizations have resulted in a massive information increase in …
records, and public health organizations have resulted in a massive information increase in …