Mr Demetris Lappas
Contact
- Email: k1838447@kingston.ac.uk
- Location: Penrhyn Road
- Faculty: Faculty of Engineering, Computing and the Environment
- School: School of Computer Science and Mathematics
- Department: Department of Computer Science
Research project: Anomaly Detection in Computer Vision using Deep Learning Models
Abstract
Anomaly detection is the practice of detecting rare patterns in data, which deviate beyond a particular distribution of expected behaviour. Anomalies by definition are rare, Automated mechanisms that are able to detect anomalies would be valuable as they have the potential to significantly reduce human operators time and therefore minimise errors and costs.
Classic machine learning approaches tackle the problem by measuring the distance between data points with respect to the area occupied by the majority of normal data. However, this is more challenging within computer vision and more sophisticated models are required to detect anomalies. My research aims to develop new models for recognising arbitrary anomalies within images and/or videos using combinations of various machine learning and deep learning techniques.
- Research degree: PhD
- Title of project: Anomaly Detection in Computer Vision using Deep Learning Models
- Research supervisor: Professor Dimitrios Makris
- Other research supervisor: Professor Vasilis Argyriou
Biography
I am PhD student working on Anomaly Detection in Computer Vision using Deep Learning Models. My research thus far has been in Image Anomaly Detection and has recently begun branching into the field of Video Anomaly Detection.
I am also a full-time professional Senior Data Scientist operating in the financial sector, where I develop Deep Learning models for Entity Resolution. I have worked for financial giants such as Barclays Bank and Ernst & Young within the departments of Cards and Payments, Financial Crime, and Entity Resolution & Data Enrichment.
Areas of research interest
- Artificial Intelligence
- Computer Vision
- Anomaly Detection
- Machine Learning
- Deep Learning
Qualifications
- BSc in Mathematics, London Metropolitan University
- Postgraduate in Mathematics, University of Glasgow
Publications
- Fourier Transformation Autoencoders for Anomaly Detection (https://ieeexplore.ieee.org/document/9415010)
- Enforced Isolation Deep Networks for Anomaly Detection in Images (https://eprints.kingston.ac.uk/id/eprint/48013/)
Jump to: Conference or Workshop Item
Number of items: 2.
Conference or Workshop Item
Lappas, Demetris, Argyriou, Vasileios and Makris, Dimitrios (2024) Dynamic distinction learning : adaptive pseudo anomalies for video anomaly detection. In: The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024; 17-21 June 2024, Seattle, U.S.. (In Press)
Lappas, Demetris, Argyriou, Vasileios and Makris, Dimitrios (2021) Fourier transformation autoencoders for anomaly detection. In: 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP); 06 - 11 Jun 2021, Toronto, Ontario, Canada (Held online).