| Real-time detection and recognition of road traffic signs J Greenhalgh, M Mirmehdi IEEE transactions on intelligent transportation systems 13 (4), 1498-1506, 2012 | 513 | 2012 |
| Assessment of Accuracy of an Artificial Intelligence Algorithm to Detect Melanoma in Images of Skin Lesions M Phillips, H Marsden, W Jaffe, RN Matin, GN Wali, J Greenhalgh, ... JAMA Network Open 2 (10), e1913436-e1913436, 2019 | 187 | 2019 |
| Recognizing text-based traffic signs J Greenhalgh, M Mirmehdi IEEE Transactions on Intelligent Transportation Systems 16 (3), 1360-1369, 2014 | 155 | 2014 |
| Detection of Malignant Melanoma Using Artificial Intelligence: An Observational Study of Diagnostic Accuracy M Phillips, J Greenhalgh, H Marsden, I Palamaras Dermatology Practical & Conceptual 10 (4), 2019 | 82 | 2019 |
| Traffic sign recognition using MSER and random forests J Greenhalgh, M Mirmehdi 2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO …, 2012 | 73 | 2012 |
| Detection and Recognition of Painted Road Surface Markings J Greenhalgh, M Mirmehdi 4th International Conference on Pattern Recognition Applications and Methods, 2015 | 28 | 2015 |
| Automatic detection and recognition of symbols and text on the road surface J Greenhalgh, M Mirmehdi Pattern Recognition: Applications and Methods: 4th International Conference …, 2015 | 21 | 2015 |
| Effectiveness of an image analyzing AI-based Digital Health Technology to identify Non-Melanoma Skin Cancer and other skin lesions: Results of the DERM-003 study H Marsden, C Morgan, S Austin, C DeGiovanni, M Venzi, P Kemos, ... Frontiers in Medicine 10, 1288521, 2023 | 9 | 2023 |
| Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance L Thomas, C Hyde, D Mullarkey, J Greenhalgh, D Kalsi, J Ko Frontiers in Medicine 10, 1264846, 2023 | 8 | 2023 |
| Assessment of accuracy of an artificial intelligence algorithm to detect melanoma in images of skin lesions. JAMA Netw Open. 2019; 2: e1913436 M Phillips, H Marsden, W Jaffe, RN Matin, GN Wali, J Greenhalgh, ... | 5 | 2019 |
| BT03 (P63) Effectiveness of an image-analysing artificial intelligence-based digital health technology to diagnose nonmelanoma skin cancer and benign skin lesions H Marsden, I Palamaras, P Kemos, J Greenhalgh British Journal of Dermatology 188 (Supplement_4), ljad113. 369, 2023 | 4 | 2023 |
| Assessment of the change in accuracy of an artificial intelligence algorithm for the detection of skin cancer in camera images following diversification and training M Phillips, J Greenhalgh | 1 | 2020 |
| Calibrating output from an image classifier J Greenhalgh, P Kemos, DB GARCIA, N Daly US Patent App. 17/934,182, 2024 | | 2024 |
| Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance D Kalsi, L Thomas, C Hyde, D Mullarkey, J Greenhalgh, JM Ko | | 2023 |
| Driver assistance using automated symbol and text recognition J Greenhalgh University of Bristol, 2015 | | 2015 |
