Dr Ahmed is an Associate Professor of Computer Vision and Image Analysis, in the School of Computer Science. Before joining the University of Nottingham, he held several research and academic positions (since 2005) in various UK universities (including Surrey and Lincoln). He also worked in the industry for several years, including in Sharp Labs of Europe (SLE), Oxford (UK), as a Research Scientist, and other Engineering Consultants companies abroad.
Amr successfully supervised a number of PhD and MSc by research students, and couple of RAs and Post-Docs on his research projects. He is a Member of the British Computer Society (MBCS) and the IEEE Computer Society. He received his Bachelor's degree in Electrical Engineering and M.Sc. degree (by research) in Computer and Systems Engineering, from Ain Shams University, Egypt, in 1993 and 1998 respectively, and his Ph.D. degree in Computer Graphics and Animation from the University of Surrey, U.K., in 2005.
Amr's main expertise is in Computer Vision, Image and Video analysis, and particularly for Medical and Health-related applications.
For more information about the current, previous, and future research areas, please have a look at Amr's blog & webpage at "http://amrahmed.net"
Taught & Teaching (including designing, developing and delivering) a range of Computer Science subjects, such as:
Digital Contents Analysis,
Amr's research interest and expertise is focused on the applications of computer vision and image/video processing for analysis, understanding, and interpretation of visual contents (Images and… read more
ABIR BAÂZAOUI, WALID BARHOUMI, AMR AHMED and EZZEDDINE ZAGROUBA, 2018. Modelling Clinician Medical-knowledge in Terms of Med-level Features for Semantic Content-based Mammogram Retrieval Expert Systems With Applications. 94, 11-20 SADDAM BEKHET and AMR AHMED, 2018. Graph-Based Video Sequence Matching Using Dominant Colour Graph Profile (DCGP) Journal of Signal, Image and Video Processing. 12(2), 291-298
YIFAN YANG, AMR AHMED, SHIGANG YUE, XIANG XIE, HONG CHEN and ZHIHUA WANG, 2017. An algorithm for accurate needle orientation. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference. 2016, 5095-5098
Keep in eye on this space: news, positions, ...etc.
All potential Collaborators, RAs, and PhD/MSc research students are very welcome to get in touch and discuss any potential research proposal/idea.
We are keen to attract highly qualified students, including internships and short-term projects/visits. Please get in touch if you are interested in joining us at any relevant level.
Amr's research interest and expertise is focused on the applications of computer vision and image/video processing for analysis, understanding, and interpretation of visual contents (Images and Videos). His current (and previous) research topics include:
- Video Analysis: Matching, Similarity, annotation, scene understanding and Semantic Analysis.
- Medical Image/Video Analysis & health-related applications, including::
- Digital Pathology (e.g. Detection and Classification of BE, Breast Cancer classification).
- CAD (Computer Aided Diagnosis) systems, e.g.:
- Liver Characterization.
- Lesion detection, segmentation, and classification.
- Personalized Health screening & monitoring (non/less-invasive approaches).
- CBIR and fusion of multimodal data for diagnosis.
- Surgery planning and Virtual Training.
- Integration of knowledge with computer vision for semantic analysis and diagnosis.
- Contents-Based Image Retrieval (CBIR).
- Handwriting recognition, especially in Arabic.
- Video Shot-boundaries detection. (Sharp-Labs)
- Automatic 3D motion editing and synthesis of realistic 3D character animation (from MOCAP).
- Handwriting Recognition (of Arabic).
- Text Analysis: Psycholinguistic, Author/group identification in forums, ...etc.
Computer Vision and Image/Video Analysis in:
- (continue) Medical & health (Pathology, Cancer, Retina,...etc.)
- Crops monitoring & grading.
- Animal monitoring.
- Food grading and quality.