Essays about: "Generative Adversarial Networks"

Showing result 6 - 10 of 143 essays containing the words Generative Adversarial Networks.

1. 6. Domain Adaptation for Multi-Contrast Image Segmentation in Cardiac Magnetic Resonance Imaging

   University essay from KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

   Author : Thomas Proudhon; [2023]
   Keywords : Cardiac Magnetic Resonance Imaging; Deep Learning; Domain Adaptation; Unsupervised Segmentation; Image-to-image Translation;

   Abstract : Accurate segmentation of the ventricles and myocardium on Cardiac Magnetic Resonance (CMR) images is crucial to assess the functioning of the heart or to diagnose patients suffering from myocardial infarction. However, the domain shift existing between the multiple sequences of CMR data prevents a deep learning model trained on a specific contrast to be used on a different sequence. READ MORE

3. 7. Using Generative Adversarial Networks for H&E-to-HER2 Stain Translation in Digital Pathology Images

   University essay from Linköpings universitet/Institutionen för medicinsk teknik

   Author : William Tirmén; [2023]
   Keywords : Machine learning; Artificial intelligence; Digital pathology; Image processing; Generative adversarial networks; Image-to-image translation;

   Abstract : In digital pathology, hematoxylin & eosin (H&E) is a routine stain which is performed on most clinical cases and it often provides clinicians with sufficient information for diagnosis. However, when making decisions on how to guide breast cancer treatment, immunohistochemical staining of human epidermal growth factor 2 (HER2 staining) is also needed. READ MORE

4. 8. Towards Building Privacy-Preserving Language Models: Challenges and Insights in Adapting PrivGAN for Generation of Synthetic Clinical Text

   University essay from Stockholms universitet/Institutionen för data- och systemvetenskap

   Author : Atena Nazem; [2023]
   Keywords : Generative Adversarial Networks; privacy-preserving language models; clinical text data; reinforcement learning; synthetic data;

   Abstract : The growing development of artificial intelligence (AI), particularly neural networks, is transforming applications of AI in healthcare, yet it raises significant privacy concerns due to potential data leakage. As neural networks memorise training data, they may inadvertently expose sensitive clinical data to privacy breaches, which can engender serious repercussions like identity theft, fraud, and harmful medical errors. READ MORE

5. 9. Technology Acceptance for AI implementations : A case study in the Defense Industry about 3D Generative Models

   University essay from KTH/Skolan för industriell teknik och management (ITM)

   Author : Michael Arenander; [2023]
   Keywords : Technology Acceptance; Artificial Intelligence; Machine Learning; 3D Generative Models; Innovation; Teknisk Acceptans; Artificiell Intelligens; Maskininlärning; 3D Generativa Modeller; Innovation;

   Abstract : Advancements in Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) has emerged into 3D object creation processes through the rise of 3D Generative Adversarial Networks (3D GAN). These networks contain 3D generative models capable of analyzing and constructing 3D objects. READ MORE

6. 10. Accuracy and Robustness of State of the Art Deepfake Detection Models

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Tobias Carlsson; Oskar Strömberg; [2023]
   Keywords : ;

   Abstract : With the evolution of artificial intelligence a lot of people have started getting worried about the potential dangers of deepfake images and videos, such as spreading fake videos of influential people. Several solutions to this problem have been proposed with some of the most efficient being convolutional neural networks for face detection in order to differentiate real images from deepfake images generated with a generative adversarial network. READ MORE