Implementación de Redes Generativas Adversarias (GANs) para la generación de imágenes de tejido humano
This project is based on the generation of images of human tissue, specifically, skin lesions such as melanoma or seborrheic keratosis, using a Generative Adversarial Network and a dataset of 2000 real images. The main application of the project in the field of medicine is to increase the global dat...
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| Format: | Master's thesis |
| Publication date: | 2019 |
| Country: | España |
| Institution: | Universitat Oberta de Catalunya (UOC) |
| Repository: | O2, repositorio institucional de la UOC |
| OAI Identifier: | oai:openaccess.uoc.edu:10609/90566 |
| Online Access: | http://hdl.handle.net/10609/90566 |
| Access Level: | Open access |
| Keyword: | disciminator GAN deep learning CNN MVP generator artificial intelligence discriminador aprenentatge profund generador intel·ligència artificial aprendizaje profundo inteligencia artificial Artificial intelligence -- TFM Intel·ligència artificial -- TFM Inteligencia artificial -- TFM |
| Summary: | This project is based on the generation of images of human tissue, specifically, skin lesions such as melanoma or seborrheic keratosis, using a Generative Adversarial Network and a dataset of 2000 real images. The main application of the project in the field of medicine is to increase the global database of images of human tissue and thus, contribute to medical studies in the dermatological area. Images with a resolution of 64x64 have been obtained and validated through a representation of reduced dimensions (PCA and tSNE) of the whole set of images, real and generated ones. |
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