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While deep learning has shown remarkable performance in medical imaging benchmarks, translating these results to real-world clinical deployment remains challenging. Models trained on data from one
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This project aims to develop robust algorithms capable of identifying and analyzing fingertips extracted from both static images and video footage. Machine learning techniques, particularly computer
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The detection of human activities is crucial for effective monitoring purposes. The challenge lies in accurately and promptly identifying various types of activities from videos and images captured
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This project aims to employ advanced machine learning techniques to analyse text, audio, images, and videos for signs of harmful behaviour. Natural language processing algorithms are utilized
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Are you interested in applying your AI/DL knowledge to the medical domain? This project focuses on the use of AI in Medical Imaging (e.g. CT, MRI, X-Ray, Ultrasound, etc). The work includes
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also explore the role of AI to guide or suggest analytics. Patient Data Analysis, Procedure Planning & Organ Segmentation: we will explore immersive XR interaction techniques for patient data
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This project aims to identify novel methods for inferring where and when photographs and videos were recorded from features of the material itself. A key requirement of image processing in a Law
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systems. The fast growth, practical achievements and the overall success of modern approaches to AI guarantees that machine learning AI approaches will prevail as a generic computing paradigm, and will find
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. This would provide thousands of diverse example images with corresponding body part locations. These data would be used to train a deep learning model 5, 7 . The model’s high-quality body part predictions may
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We have a range of potential research projects on offer in partnership with VIFM - https://www.vifm.org/ - looking at ML techniques in predicting forensic diagnoses / image analysis, across