Contact Dr Lichao Yang
Areas of expertise
- Computing, Simulation & Modelling
- Human Factors
Background
Dr Lichao Yang received his PhD degree from Cranfield University in 2022. He has a background in automotive engineering. He received his BEng in automotive engineering from Coventry University and MSc in automotive mechatronics from Cranfield University.
Current activities
Lichao is a research fellow in computer vision and artificial intelligence. He is currently working on the project of developing artificial intelligence-based methods for the construction site to improve productivity and reduce greenhouse gas emissions. His research interests are Computer vision, Image processing, Deep learning, machine learning, Human behaviour analysis.
Publications
Articles In Journals
- Wang S, Yang L, Zhang Z & Zhao Y. (2024). Keypoints-based Heterogeneous Graph Convolutional Networks for construction. Expert Systems with Applications, 237(March)
- Cao J, Yang L, Sarrigiannis PG, Blackburn D & Zhao Y. (2024). Dementia classification using a graph neural network on imaging of effective brain connectivity. Computers in Biology and Medicine, 168
- Wang Y, Liu H, Yang L, Durazo-Cardenas I, Namoano B, .... (2024). A full 3D reconstruction of rail tracks using a camera array. Measurement, 225
- Deng K, Liu H, Cao J, Yang L, Du W, .... (2024). Attention mechanism enhanced spatiotemporal-based deep learning approach for classifying barely visible impact damages in CFRP materials. Composite Structures, 337
- Deng K, Liu H, Yang L, Addepalli S & Zhao Y. (2023). Classification of barely visible impact damage in composite laminates using deep learning and pulsed thermographic inspection. Neural Computing and Applications, 35(15)
- Yang L, Du W & Zhao Y. (2023). A lightweight temporal attention-based convolution neural network for driver's activity recognition in edge. Computers and Electrical Engineering, 110(September)
- Yang L, Shan X, Lv C, Brighton J & Zhao Y. (2022). Learning Spatio-Temporal Representations With a Dual-Stream 3-D Residual Network for Nondriving Activity Recognition. IEEE Transactions on Industrial Electronics, 69(7)
- Zhou J, Du W, Yang L, Deng K, Addepalli S, .... (2022). Pattern Recognition of Barely Visible Impact Damage in Carbon Composites Using Pulsed Thermography. IEEE Transactions on Industrial Informatics, 18(10)
- Yang L, Babayi Semiromi M, Xing Y, Lv C, Brighton J, .... (2022). The Identification of Non-Driving Activities with Associated Implication on the Take-Over Process. Sensors, 22(1)
- Liu H, Li W, Yang L, Deng K & Zhao Y. (2022). Automatic reconstruction of irregular shape defects in pulsed thermography using deep learning neural network. Neural Computing and Applications, 34(24)
- Yang L, Dong K, Ding Y, Brighton J, Zhan Z, .... (2021). Recognition of visual-related non-driving activities using a dual-camera monitoring system. Pattern Recognition, 116(August)
- Shan X, Huo S, Yang L, Cao J, Zou J, .... (2021). A Revised Hilbert-Huang Transformation to Track Non-Stationary Association of Electroencephalography Signals. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 29
- Wang Z, Wu Y, Yang L, Thirunavukarasu A, Evison C, .... (2021). Fast Personal Protective Equipment Detection for Real Construction Sites Using Deep Learning Approaches. Sensors, 21(10)
- Wang S, Mei J, Yang L & Zhao Y. (2021). Infer Thermal Information from Visual Information: A Cross Imaging Modality Edge Learning (CIMEL) Framework. Sensors, 21(22)
- Yang L, Yang T-Y, Liu H, Shan X, Brighton J, .... (2021). A Refined Non-Driving Activity Classification Using a Two-Stream Convolutional Neural Network. IEEE Sensors Journal, 21(14)
- Yang L, Dong K, Dmitruk AJ, Brighton J & Zhao Y. (2020). A Dual-Cameras-Based Driver Gaze Mapping System With an Application on Non-Driving Activities Monitoring. IEEE Transactions on Intelligent Transportation Systems, 21(10)
Conference Papers
- Wang Y, Yang L, Korek WT, Zhao Y & Li W-C. (2023). The Evaluations of the Impact of the Pilot’s Visual Behaviours on the Landing Performance by Using Eye Tracking Technology
- Yang L, Semiromi MB, Auger D, Dmitruk A, Brighton J, .... (2020). The implication of non-driving activities on situation awareness and take-over performance in level 3 automation
Books
- Zhao Y, Lv C & Yang L. (2023). Human-Machine Interaction for Automated Vehicles
- Zhao Y, Lv C & Yang L. (2023). The implication of non-driving tasks on the take-over process In Human-Machine Interaction for Automated Vehicles. Elsevier.
- Zhao Y, Lv C & Yang L. (2023). Introduction In Human-Machine Interaction for Automated Vehicles. Elsevier.
- Zhao Y, Lv C & Yang L. (2023). Driver workload estimation In Human-Machine Interaction for Automated Vehicles. Elsevier.
- Zhao Y, Lv C & Yang L. (2023). Real-time driver behaviour recognition In Human-Machine Interaction for Automated Vehicles. Elsevier.
- Zhao Y, Lv C & Yang L. (2023). Intelligent haptic interface design for human–machine interaction in automated vehicles In Human-Machine Interaction for Automated Vehicles. Elsevier.
- Zhao Y, Lv C & Yang L. (2023). Driver behaviour recognition based on hand-gesture In Human-Machine Interaction for Automated Vehicles. Elsevier.
- Zhao Y, Lv C & Yang L. (2023). Driver behaviour recognition based on eye gaze In Human-Machine Interaction for Automated Vehicles. Elsevier.
- Zhao Y, Lv C & Yang L. (2023). Driver behaviour recognition based on head movement In Human-Machine Interaction for Automated Vehicles. Elsevier.
- Zhao Y, Lv C & Yang L. (2023). Driver behaviour recognition based on the fusion of head movement and hand movement In Human-Machine Interaction for Automated Vehicles. Elsevier.
- Zhao Y, Lv C & Yang L. (2023). Driver steering intention prediction using neuromuscular dynamics In Human-Machine Interaction for Automated Vehicles. Elsevier.
- Zhao Y, Lv C & Yang L. (2023). Neuromuscular dynamics characterisation for human–machine interface In Human-Machine Interaction for Automated Vehicles. Elsevier.