Year: 2024
Type: conference-paper
Abstract: With the rapid advancement of modern science and technology, the importance of multi-sensor data fusion technology in various applications has become increasingly prominent. However, traditional non-intelligent fusion methods reveal many shortcomings when dealing with complex and dynamic environments. These methods rely on preset models and algorithms, showing poor adaptability to system nonlinearities, time-varying characteristics, and uncertainties, making it challenging to achieve real-time, efficient, and accurate information fusion. Moreover, traditional methods often struggle with processing multi-source heterogeneous data, being easily affected by noise and interference, thus reducing fusion accuracy and system robustness.
Authors: Huhai Jiang, Huimeng Ke
Institution: Southwestern Institute of Physics
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4405849270