Oct 1, 2025 · With the emergence of next-generation deep learning models such as diffusion models, Mamba-based state space architectures, and large language models (LLMs), the landscape of multi …

Dec 1, 2023 · This section discusses several popular applications based on deep multi-sensor fusion learning, including medical diagnosis, automotive driving, remote sensing, and intelligent robotics.

Although some provide interesting suggestions for computer vision and medical applications, most of the proposed methodologies discussed in this Special Issue are focused on applications in sensor data …

This paper first formalizes multi-sensor fusion strategies into data-level, feature-level, and decision-level cate-gories and then provides a systematic review of deep learning-based methods corresponding to …

Aug 8, 2025 · From 2011 to 2020, the widespread adoption of deep learning transformed the field driving some major breakthroughs in the autonomous vehicles domain. A key contribution of this work is the …

Jan 10, 2026 · About this book This book focuses on the development of multisensor fusion algorithms for wearable devices that are useful in ambulatory health monitoring using signal-processing and …

Jan 7, 2026 · A recent survey on radar and vision methods 15 provides a detailed taxonomy of deep-learning-based fusion strategies, demonstrating radar’s growing importance in robust perception.

The combination of artificial intelligence and sensor fusion is opening hitherto unheard-of prospects in several fields. The architectures, models, and deep learning techniques used in intelligent sensor …

Feb 27, 2025 · Deep learning models are being used to automate and optimize the fusion process. Integrating data from diverse sensors, such as visual, thermal, and acoustic, for richer insights.

Jul 29, 2020 · Specifically, it focuses on recent studies that use deep learning sensor fusion algorithms for perception, localization, and mapping.