All Outputs (23)

Data Augmentation via Mixed Class Interpolation using Cycle-Consistent Generative Adversarial Networks Applied to Cross-Domain Imagery (2021)
Presentation / Conference Contribution
Sasaki, H., Willcocks, C., & Breckon, T. (2021, January). Data Augmentation via Mixed Class Interpolation using Cycle-Consistent Generative Adversarial Networks Applied to Cross-Domain Imagery. Presented at 25th International Conference on Pattern Recognition (ICPR 2020), Milan, Italy

Machine learning driven object detection and classification within non-visible imagery has an important role in many fields such as night vision, all-weather surveillance and aviation security. However, such applications often suffer due to the limit... Read More about Data Augmentation via Mixed Class Interpolation using Cycle-Consistent Generative Adversarial Networks Applied to Cross-Domain Imagery.

Multi-Class 3D Object Detection Within Volumetric 3D Computed Tomography Baggage Security Screening Imagery (2021)
Presentation / Conference Contribution
Wang, Q., Bhowmik, N., & Breckon, T. (2020, December). Multi-Class 3D Object Detection Within Volumetric 3D Computed Tomography Baggage Security Screening Imagery. Presented at 19th IEEE International Conference on Machine Learning and Applications (ICMLA 2020), Miami, Florida

Automatic detection of prohibited objects within passenger baggage is important for aviation security. X-ray Computed Tomography (CT) based 3D imaging is widely used in airports for aviation security screening whilst prior work on automatic prohibite... Read More about Multi-Class 3D Object Detection Within Volumetric 3D Computed Tomography Baggage Security Screening Imagery.

Efficient and Compact Convolutional Neural Network Architectures for Non-temporal Real-time Fire Detection (2021)
Presentation / Conference Contribution
Thomson, W., Bhowmik, N., & Breckon, T. (2020, December). Efficient and Compact Convolutional Neural Network Architectures for Non-temporal Real-time Fire Detection. Presented at 19th IEEE International Conference on Machine Learning and Applications (ICMLA 2020), Miami, FL

Automatic visual fire detection is used to complement traditional fire detection sensor systems (smoke/heat). In this work, we investigate different Convolutional Neural Network (CNN) architectures and their variants for the non-temporal real-time bo... Read More about Efficient and Compact Convolutional Neural Network Architectures for Non-temporal Real-time Fire Detection.