14:00 – 14:15 Welcome and Introduction: Professor John Murray
14:15 – 14:45 Guest Speaker: Robert Kidd, UK Home Office
14:45 – 15:45 Oral Session 1
1. The Good, the Bad and the Ugly: Evaluating Convolutional Neural Networks for Prohibited Item Detection Using Real and Synthetically Composited X-ray Imagery; Neelanjan Bhowmi, Qian Wang, Yona Falinie A. Gaus, Marcin Szarek, Toby Breckon
2. DCNNs: A Transfer Learning comparison of Full Weapon Family threat detection for Dual-Energy X-Ray Baggage Imagery; Ashley C Williamson, Patrick Dickinson, Tryphon Lambrou, John C Murray
3. Using Manifold Embedding for Automatic Threat Detection: An Alternative Machine Learning Approach; Roberta Piroddi, Elias Griffith, Yannis Goulermas, Simon Maskell, Jason Ralph
15:45 – 16:30 Coffee Break/Poster* Session
16:30 – 17:30 Oral Session 2
1. MRCNet: Crowd Counting and Density Map Estimation in Aerial and Ground Imagery; Reza Bahmanyar, Eleonora Vig, Peter Reinartz
2. Foreground object detection enhancement by adaptive super resolution for video surveillance; Miguel A. Molina Cabello, David A. Elizondo, Rafael Marcos Luque-Baena, Ezequiel López-Rubio
3. SP-NET: One Shot Fingerprint Singular-Point Detector ; Geetika Arora, Ranjeet Ranjan Jha, Akash Agrawal, Kamlesh Tiwari, Aditya Nigam
17:30 – 18:00 Panel discussion (Murray, Ralph, Breckon, Kidd) and conclusion
*Posters:
1. HMMN: Hard Sample Mining Memory Network for Re-identification; Qing Li, Pengcheng Han, Shuhui Bu, Ke Li
2. A low-power end-to-end hybrid neuromorphic framework for surveillance applications; Andres Camillo Ussa Caycedo, Luca Della Vedova, Vandana Reddy Padala, Deepak Singla, Jyotibdha Acharya, Charles Zhang Lei, Garrick Orchard, Arindam Basu, Bharath Ramesh
3. Feature Map Random Transfer-based Heterogeneous Data Fusion for Pedestrian Detection in Far IR Images; Junhwan Ryu, Sungho Kim
4. Homography estimation with deep convolutional neural networks by random color transformations; Miguel A. Molina Cabello, David A. Elizondo, Rafael Marcos Luque-Baena, Ezequiel López-Rubio
5. A deep learning based autonomous distance estimation and tracking of multiple objects for improvement in safety and security in railways; Muhammad Abdul Haseeb, Danijela Ristic-Durrant, Axel Gräser