Generative Adversarial Network for Generation of Artificial Microwave Data for Stroke Detection

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dc.contributor.authorEkblom, Ebba
dc.contributor.authorSvensson, Rebecca
dc.contributor.departmentChalmers tekniska högskola / Institutionen för fysiksv
dc.contributor.examinerGustafsson, Kristian
dc.contributor.supervisorJonasson Svärdsby, Albin
dc.contributor.supervisorHilkert, Ann-Sophie
dc.date.accessioned2021-06-16T08:52:15Z
dc.date.available2021-06-16T08:52:15Z
dc.date.issued2021sv
dc.date.submitted2020
dc.description.abstractThis study aims to explore the possibilities of generating microwave data with a Generative Adversarial Network (GAN), in order to expand the existing data set and increase the performance of a stroke detection algorithm. Key challenges of the project relate to the small data set size and samples with many features. The generation of data was done with a Conditional Wasserstein Generative Adversarial Network. Due to the low data regime, the effects of adding DeLiGAN was also investigated. In addition to generating data with a GAN, this study also covers methods for the evaluation of generated data. To evaluate the quality of the generated data, a separate classifier network is utilised. Evaluation of the generated data in classification problems, as well as visualisation of distribution coverage, indicate that the data is of good quality and represent the distribution of original data well. However, results also show that the generated data cannot completely substitute the real data, and is deemed to be lacking in some quality measure. Still, the results are promising and the project concludes that it certainly is possible to generate microwave data which is to be used for stroke detection, with great potential for further improvements.sv
dc.identifier.coursecodeTIFX05sv
dc.identifier.urihttps://hdl.handle.net/20.500.12380/302553
dc.language.isoengsv
dc.setspec.uppsokPhysicsChemistryMaths
dc.subjectGenerative Adversarial Networkssv
dc.subjectWasserstein GANsv
dc.subjectConditional GANsv
dc.subjectDeLiGANsv
dc.subjectmicrowavesv
dc.subjecthaemorrhagic strokesv
dc.titleGenerative Adversarial Network for Generation of Artificial Microwave Data for Stroke Detectionsv
dc.type.degreeExamensarbete för masterexamensv
dc.type.uppsokH
local.programmeComplex adaptive systems (MPCAS), MSc
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