All Outputs (3)

On the Impact of Using X-Ray Energy Response Imagery for Object Detection via Convolutional Neural Networks (2021)
Presentation / Conference Contribution
Bhowmik, N., Gaus, Y., & Breckon, T. (2021, September). On the Impact of Using X-Ray Energy Response Imagery for Object Detection via Convolutional Neural Networks. Presented at International Conference on Image Processing, Anchorage, AK

Automatic detection of prohibited items within complex and cluttered X-ray security imagery is essential to maintaining transport security, where prior work on automatic prohibited item detection focus primarily on pseudo-colour (rgb) X-ray imagery.... Read More about On the Impact of Using X-Ray Energy Response Imagery for Object Detection via Convolutional Neural Networks.

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.