Artificial intelligence‐enabled sensing technologies in the 5G/internet of things era: from virtual reality/augmented reality to the digital twin

Z Zhang, F Wen, Z Sun, X Guo, T He… - Advanced Intelligent …, 2022 - Wiley Online Library
With the development of 5G and Internet of Things (IoT), the era of big data‐driven product
design is booming. In addition, artificial intelligence (AI) is also emerging and evolving by …

Review the state-of-the-art technologies of semantic segmentation based on deep learning

Y Mo, Y Wu, X Yang, F Liu, Y Liao - Neurocomputing, 2022 - Elsevier
The goal of semantic segmentation is to segment the input image according to semantic
information and predict the semantic category of each pixel from a given label set. With the …

Milestones in autonomous driving and intelligent vehicles: Survey of surveys

L Chen, Y Li, C Huang, B Li, Y Xing… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace
due to the convenience, safety, and economic benefits. Although a number of surveys have …

How can artificial intelligence impact sustainability: A systematic literature review

AK Kar, SK Choudhary, VK Singh - Journal of Cleaner Production, 2022 - Elsevier
We need a proper mechanism to manage issues related to our environment, economy, and
society to proceed toward sustainability. Many researchers have worked for sustainable …

A survey on multimodal large language models for autonomous driving

C Cui, Y Ma, X Cao, W Ye, Y Zhou… - Proceedings of the …, 2024 - openaccess.thecvf.com
With the emergence of Large Language Models (LLMs) and Vision Foundation Models
(VFMs), multimodal AI systems benefiting from large models have the potential to equally …

Sensor and sensor fusion technology in autonomous vehicles: A review

DJ Yeong, G Velasco-Hernandez, J Barry, J Walsh - Sensors, 2021 - mdpi.com
With the significant advancement of sensor and communication technology and the reliable
application of obstacle detection techniques and algorithms, automated driving is becoming …

Challenges in deploying machine learning: a survey of case studies

A Paleyes, RG Urma, ND Lawrence - ACM computing surveys, 2022 - dl.acm.org
In recent years, machine learning has transitioned from a field of academic research interest
to a field capable of solving real-world business problems. However, the deployment of …

Developing future human-centered smart cities: Critical analysis of smart city security, Data management, and Ethical challenges

K Ahmad, M Maabreh, M Ghaly, K Khan, J Qadir… - Computer Science …, 2022 - Elsevier
As the globally increasing population drives rapid urbanization in various parts of the world,
there is a great need to deliberate on the future of the cities worth living. In particular, as …

Deep reinforcement learning for autonomous driving: A survey

BR Kiran, I Sobh, V Talpaert, P Mannion… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
With the development of deep representation learning, the domain of reinforcement learning
(RL) has become a powerful learning framework now capable of learning complex policies …

Review of deep learning: concepts, CNN architectures, challenges, applications, future directions

L Alzubaidi, J Zhang, AJ Humaidi, A Al-Dujaili… - Journal of big Data, 2021 - Springer
In the last few years, the deep learning (DL) computing paradigm has been deemed the
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …