Fieguth, Paul

A review of uncertainty quantification in deep learning: Techniques, applications and challenges

Abdar, M., Pourpanah, F., Hussain, S., Rezazadegan, D., Liu, L., Ghavamzadeh, M., Fieguth, P., Cao, X., Khosravi, A., Acharya, U. R., et al. (2021) · Information Fusion

Adversarial Robustness in Machine LearningGaussian Processes and Bayesian Inference

Cited by 3,111

Deep Learning for Generic Object Detection: A Survey

Liu, L., Ouyang, W., Wang, X., Fieguth, P., Chen, J., Liu, X., & Pietikäinen, M. (2018) · arXiv

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 2,965

Deep Learning for Generic Object Detection: A Survey

Liu, L., Ouyang, W., Wang, X., Fieguth, P., Chen, J., Liu, X., & Pietikäinen, M. (2020) · International Journal of Computer Vision

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 2,965

A review on computer vision based defect detection and condition assessment of concrete and asphalt civil infrastructure

Koch, C., Georgieva, K., Kasireddy, V., Akinci, B., & Fieguth, P. (2015) · Advanced Engineering Informatics

Infrastructure Maintenance and MonitoringIndustrial Vision Systems and Defect Detection

Cited by 1,065

Local binary features for texture classification: Taxonomy and experimental study

Liu, L., Fieguth, P., Guo, Y., Wang, X., & Pietikäinen, M. (2017) · Pattern Recognition

Image Retrieval and Classification TechniquesRadiomics and Machine Learning in Medical Imaging

Cited by 369