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All Outputs (8)

GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training (2018)
Presentation / Conference Contribution
Akcay, S., Atapour-Abarghouei, A., & Breckon, T. P. (2018, December). GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training. Presented at 14th Asian Conference on Computer Vision (ACCV)., Perth, Australia

Anomaly detection is a classical problem in computer vision, namely the determination of the normal from the abnormal when datasets are highly biased towards one class (normal) due to the insufficient sample size of the other class (abnormal). While... Read More about GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training.

On the Impact of Illumination-Invariant Image Pre-transformation on Contemporary Automotive Semantic Scene Understanding (2018)
Presentation / Conference Contribution
Alshammari, N., Akcay, S., & Breckon, T. (2018, June). On the Impact of Illumination-Invariant Image Pre-transformation on Contemporary Automotive Semantic Scene Understanding. Presented at 29th IEEE Intelligent Vehicles Symposium (IEEE IV 2018)., Changshu, Suzhou, China

Illumination changes in outdoor environments under non-ideal weather conditions have a negative impact on automotive scene understanding and segmentation performance. In this paper, we present an evaluation of illuminationinvariant image transforms a... Read More about On the Impact of Illumination-Invariant Image Pre-transformation on Contemporary Automotive Semantic Scene Understanding.

Real-time Classification of Vehicle Types within Infra-red Imagery (2016)
Presentation / Conference Contribution
Kundegorski, M., Akcay, S., Payen de La Garanderie, G., Breckon, T., & Stokes, R. (2016, November). Real-time Classification of Vehicle Types within Infra-red Imagery. Presented at Optics and Photonics for Counterterrorism, Crime Fighting and Defence XII, Edinburgh, United Kingdom

Real-time classification of vehicles into sub-category types poses a significant challenge within infra-red imagery due to the high levels of intra-class variation in thermal vehicle signatures caused by aspects of design, current operating duration... Read More about Real-time Classification of Vehicle Types within Infra-red Imagery.

Transfer Learning Using Convolutional Neural Networks For Object Classification Within X-Ray Baggage Security Imagery (2016)
Presentation / Conference Contribution
Akcay, S., Kundegorski, M., Devereux, M., & Breckon, T. (2016, September). Transfer Learning Using Convolutional Neural Networks For Object Classification Within X-Ray Baggage Security Imagery. Presented at 2016 IEEE International Conference on Image Processing., Phoenix, AZ, USA

We consider the use of transfer learning, via the use of deep Convolutional Neural Networks (CNN) for the image classification problem posed within the context of X-ray baggage security screening. The use of a deep multi-layer CNN approach, tradition... Read More about Transfer Learning Using Convolutional Neural Networks For Object Classification Within X-Ray Baggage Security Imagery.

On using Feature Descriptors as Visual Words for Object Detection within X-ray Baggage Security Screening (2016)
Presentation / Conference Contribution
Kundegorski, M., Akcay, S., Devereux, M., Mouton, A., & Breckon, T. (2016, January). On using Feature Descriptors as Visual Words for Object Detection within X-ray Baggage Security Screening. Presented at International Conference on Imaging for Crime Detection and Prevention, Madrid, Spain

Here we explore the use of various feature point descriptors as visual word variants within a Bag-of-Visual-Words (BoVW) representation scheme for image classification based threat detection within baggage security X-ray imagery. Using a classical Bo... Read More about On using Feature Descriptors as Visual Words for Object Detection within X-ray Baggage Security Screening.