Sökning: "generative adversarial learning"
Visar resultat 1 - 5 av 8 uppsatser innehållade orden generative adversarial learning.
- Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datalogi och datorsystemteknik
Sammanfattning : Machine Learning is a fast growing area that revolutionizes computer programs by providing systems with the ability to automatically learn and improve from experience. In most cases, the training process begins with extracting patterns from data. The data is a key factor for machine learning algorithms, without data the algorithms will not work. LÄS MER
- Master-uppsats, Lunds universitet/Matematik LTH
Sammanfattning : This thesis was written at CellaVision who sells digital microscope systems, mainly used for blood analysis. Blood tests are an important part of modern health care and today digital microscopes are widely used to replace conventional microscopy. LÄS MER
- Uppsats för yrkesexamina på avancerad nivå, KTH/Skolan för elektroteknik och datavetenskap (EECS)
Sammanfattning : The Generative Adversarial Network framework has shown success in implicitly modeling data distributions and is able to generate realistic samples. Its architecture is comprised of a generator, which produces fake data that superficially seem to belong to the real data distribution, and a discriminator which is to distinguish fake from genuine samples. LÄS MER
- Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)
Sammanfattning : Image Super resolution is a widely-studied problem in computer vision, where the objective is to convert a lowresolution image to a high resolution image. Conventional methods for achieving super-resolution such as image priors, interpolation, sparse coding require a lot of pre/post processing and optimization. LÄS MER
- Master-uppsats, Linköpings universitet/Datorseende; Linköpings universitet/Datorseende
Sammanfattning : In this thesis we study a perception problem in the context of autonomous driving. Specifically, we study the computer vision problem of 3D object detection, in which objects should be detected from various sensor data and their position in the 3D world should be estimated. LÄS MER
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