University of Twente Student Theses
Real-time skin cancer detection using neural networks on an embedded device
Veneman, R. (2021) Real-time skin cancer detection using neural networks on an embedded device.
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| Abstract: | Skin cancer is one of the most common types of cancer there is. Skin cancer develops on the skin and can spread to other areas of the body possibly causing extensive damage. The earlier the cancer is treated the better the changes are of survival. Since skin cancer grows on the outer layer of the skin, it can be diagnosed by a trained eye. Each type of skin cancer has certain visual characteristics which makes it possible for Artificial Intelligence (AI) to determine whether a tumour is a specific type of cancer or whether it is a benign tumour. However, many people do not know how to recognize skin cancer and people might not be inclined to visit a doctor for a simple discolouring on the skin. This research paper will try and develop a smartphone application that can detect skin tumour in real-time using object detection. Additionally, it will also be able to classify skin cancer from a single image using a trained Convolutional Neural Network (CNN). |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 30 exact sciences in general, 44 medicine, 54 computer science |
| Programme: | Business & IT BSc (56066) |
| Link to this item: | https://purl.utwente.nl/essays/87429 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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