The project "Ultra-layered perception with brain-inspired information processing for vehicle collision avoidance" is funded by the European Union’s Horizon 2020 research and innovation programme. Its primary objective of this project is to develop a trustworthy vehicle collision detection system inspired by animals’ visual brain via trans-institutional collaboration. Processing multiple modalities sensor data inputs, such as vision and thermal maps with innovative visual brain-inspired algorithms, the project will embrace multidisciplinary and cross-continental academia and industry cooperation in the field of bio-inspired visual neural systems via neural physiological experiments, software simulation, hardware realisation and system integration. The innovative brain-inspired collision detection system has the advantages of low-cost spatial-temporal and parallel computing capacity of visual neural systems and can be realised in chips specifically for collision detection, both in normal and in complex and/or in extreme environments.
- Jin Xiao, Yanlin Jia, Xiaoyi Jiang, Shouyang Wang: Circular complex-valued GMDH-type neural network for real-valued classification problems. IEEE Transactions on Neural Networks and Learning Systems, 31(12): 5285-5299, 2020. PDF
- Jin Xiao, Yuhang Tian, Ling Xie, Xiaoyi Jiang, Jing Huang: A hybrid classification framework based on clustering. IEEE Transactions on Industrial Informatics 16(4): 2177-2188, 2020. PDF