A systematic review of Green AI

R Verdecchia, J Sallou, L Cruz - Wiley Interdisciplinary Reviews …, 2023‏ - Wiley Online Library
With the ever‐growing adoption of artificial intelligence (AI)‐based systems, the carbon
footprint of AI is no longer negligible. AI researchers and practitioners are therefore urged to …

Autonomous vehicles enabled by the integration of IoT, edge intelligence, 5G, and blockchain

A Biswas, HC Wang - Sensors, 2023‏ - mdpi.com
The wave of modernization around us has put the automotive industry on the brink of a
paradigm shift. Leveraging the ever-evolving technologies, vehicles are steadily …

Sustainable ai: Environmental implications, challenges and opportunities

CJ Wu, R Raghavendra, U Gupta… - Proceedings of …, 2022‏ - proceedings.mlsys.org
This paper explores the environmental impact of the super-linear growth trends for AI from a
holistic perspective, spanning Data, Algorithms, and System Hardware. We characterize the …

Trustworthy ai: A computational perspective

H Liu, Y Wang, W Fan, X Liu, Y Li, S Jain, Y Liu… - ACM Transactions on …, 2022‏ - dl.acm.org
In the past few decades, artificial intelligence (AI) technology has experienced swift
developments, changing everyone's daily life and profoundly altering the course of human …

Edge intelligence: Paving the last mile of artificial intelligence with edge computing

Z Zhou, X Chen, E Li, L Zeng, K Luo… - Proceedings of the …, 2019‏ - ieeexplore.ieee.org
With the breakthroughs in deep learning, the recent years have witnessed a booming of
artificial intelligence (AI) applications and services, spanning from personal assistant to …

Trustworthy graph neural networks: Aspects, methods, and trends

H Zhang, B Wu, X Yuan, S Pan, H Tong… - Proceedings of the …, 2024‏ - ieeexplore.ieee.org
Graph neural networks (GNNs) have emerged as a series of competent graph learning
methods for diverse real-world scenarios, ranging from daily applications such as …

A survey on multi-objective hyperparameter optimization algorithms for machine learning

A Morales-Hernández, I Van Nieuwenhuyse… - Artificial Intelligence …, 2023‏ - Springer
Hyperparameter optimization (HPO) is a necessary step to ensure the best possible
performance of Machine Learning (ML) algorithms. Several methods have been developed …

Energy-efficient edge based real-time healthcare support system

S Abirami, P Chitra - Advances in computers, 2020‏ - Elsevier
The ubiquitous usage of wearable IoT (wIoT) devices has created a formidable opportunity
for remote health monitoring system to provide paramount services such as preventive care …

Single-path nas: Designing hardware-efficient convnets in less than 4 hours

D Stamoulis, R Ding, D Wang… - … Conference on Machine …, 2019‏ - Springer
Can we automatically design a Convolutional Network (ConvNet) with the highest image
classification accuracy under the latency constraint of a mobile device? Neural architecture …

Edge-AI-driven framework with efficient mobile network design for facial expression recognition

Y Wu, L Zhang, Z Gu, H Lu, S Wan - ACM Transactions on Embedded …, 2023‏ - dl.acm.org
Facial Expression Recognition (FER) in the wild poses significant challenges due to realistic
occlusions, illumination, scale, and head pose variations of the facial images. In this article …