Sökning: "DCGAN"
Visar resultat 1 - 5 av 9 uppsatser innehållade ordet DCGAN.
1. Exploring State-of-the-Art Machine Learning Methods for Quantifying Exercise-induced Muscle Fatigue
Uppsats för yrkesexamina på avancerad nivå, Högskolan i Halmstad/Akademin för informationsteknologiSammanfattning : Muscle fatigue is a severe problem for elite athletes, and this is due to the long resting times, which can vary. Various mechanisms can cause muscle fatigue which signifies that the specific muscle has reached its maximum force and cannot continue the task. LÄS MER
2. GAN-Based Counterfactual Explanation on Images
Magister-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskapSammanfattning : Machine learning models are widely used in various industries. However, the black-box nature of the model limits users’ understanding and trust in its inner workings, and the interpretability of the model becomes critical. LÄS MER
3. Impact of GAN methods for theHandwritten Digit Classification inHandwritten Document Images
Magister-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskapSammanfattning : Background: GANs are well-known for their ability to generate realistic fake sample data, which can be audio, images, and videos. The application areas of GANs have increased their popularity in recent years. The first and best feature of GANs is their learning nature, characterized by powerful learning. LÄS MER
4. An empirical comparison of generative capabilities of GAN vs VAE
Kandidat-uppsats, KTH/DatavetenskapSammanfattning : Generative models are a family of machine learning algorithms that are aspire to enable computers to understand the real world. Their capability to understand the underlying distribution of data enables them to generate synthetic data from the data they are trained on. LÄS MER
5. Basil-GAN
Master-uppsats, KTH/Matematisk statistikSammanfattning : Developments in computer vision has sought to design deep neural networks which trained on a large set of images are able to generate high quality artificial images which share semantic qualities with the original image set. A pivotal shift was made with the introduction of the generative adversarial network (GAN) by Goodfellow et al.. LÄS MER