On The Impact Of Varying Region Proposal Strategies For Raindrop Detection And Classification Using Convolutional Neural Networks

Guo, T.; Akcay, S.; Adey, P.; Breckon, T.P.

doi:10.1109/ICIP.2018.8451453

All Outputs (3)

GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training (2018)
Conference Proceeding
Akcay, S., Atapour-Abarghouei, A., & Breckon, T. P. (2019). GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training. In C. Jawahar, H. Li, G. Mori, & K. Schindler (Eds.), Computer Vision – ACCV 2018 : 14th Asian Conference on Computer Vision, Perth, Australia, December 2–6, 2018, Revised Selected Papers, Part III (622-637). https://doi.org/10.1007/978-3-030-20893-6_39

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)
Conference Proceeding
Alshammari, N., Akcay, S., & Breckon, T. (2018). On the Impact of Illumination-Invariant Image Pre-transformation on Contemporary Automotive Semantic Scene Understanding. In Proc. Intelligent Vehicles Symposium (1027-1032). https://doi.org/10.1109/IVS.2018.8500664

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.

On The Impact Of Varying Region Proposal Strategies For Raindrop Detection And Classification Using Convolutional Neural Networks (2018)
Conference Proceeding
Guo, T., Akcay, S., Adey, P., & Breckon, T. (2018). On The Impact Of Varying Region Proposal Strategies For Raindrop Detection And Classification Using Convolutional Neural Networks. In Proc. Int. Conf. on Image Processing (3413-3417). https://doi.org/10.1109/ICIP.2018.8451453