A review that categorizes XAI techniques and surveys medical applications across vision, audio, and multimodal data, with an analysis of current challenges.
Integrating Generative Artificial Intelligence in Intelligent Vehicle Systems
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
This paper aims to serve as a comprehensive guide for researchers and practitioners, offering insights into the current state, potential applications, and future research directions for generative artificial intelligence and foundation models within the context of intelligent vehicles. As the automotive industry progressively integrates AI, generative artificial intelligence technologies hold the potential to revolutionize user interactions, delivering more immersive, intuitive, and personalised in-car experiences. We provide an overview of current applications of generative artificial intelligence in the automotive domain, emphasizing speech, audio, vision, and multimodal interactions. We subsequently outline critical future research areas, including domain adaptability, alignment, multimodal integration and others, as well as, address the challenges and risks associated with ethics. By fostering collaboration and addressing these research areas, generative artificial intelligence can unlock its full potential, transforming the driving experience and shaping the future of intelligent vehicles.
fields
cs.LG 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Explainable Artificial Intelligence for Medical Applications: A Review
A review that categorizes XAI techniques and surveys medical applications across vision, audio, and multimodal data, with an analysis of current challenges.