Sökning: "Synthetic image generation"

Visar resultat 1 - 5 av 33 uppsatser innehållade orden Synthetic image generation.

1. 1. AI-based image generation: The impact of fine-tuning on fake image detection

   Kandidat-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

   Författare :Nick Hagström; Anders Rydberg; [2024]
   Nyckelord :Fake image detection; LoRA; DreamBooth; Stable Diffusion; Image generation;

   Sammanfattning : Machine learning-based image generation models such as Stable Diffusion are now capable of generating synthetic images that are difficult to distinguish from real images, which gives rise to a number of legal and ethical concerns. As a potential measure of mitigation, it is possible to train neural networks to detect the digital artifacts present in the images synthesized by many generative models. LÄS MER

3. 2. Image Quality Assessment Pipeline and Semi-Automated Annotation method for Synthetic Data

   Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :Liam Le Tran; Edina Dedovic; [2023-10-24]
   Nyckelord :Facial Expression Recognition; FACS; Action Units; styleGAN2-ada; synthetic data; Image Quality Assessment; Multi-stage Pre-training; Pipeline Processing; Semi-automated Human Annotation;

   Sammanfattning : Predicting human emotions through facial expression, particularly in relation to medication field such as clinical trial settings, has garnered scientific interest in recent years due to significant understanding of the impact of treatment on emotions and social functioning. This thesis aims to improve performance of a FER model using large scale of synthetic data. LÄS MER

4. 3. Analyzing the Influence of Synthetic andAugmented Data on Segmentation Model

   Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Författare :Alex Peschel; [2023]
   Nyckelord :Artificial Intelligence; Microorganisms; Segmentation; Synthesizing; Augmentation;

   Sammanfattning : The field of Artificial Intelligence (AI) has experienced unprecedented growth in recent years, thanks to the numerous applications related to speech recognition, natural language processing, and computer vision. However, one of the challenges facing AI is the requirement for large amounts of energy, time, and data to be effective and accurate. LÄS MER

5. 4. Multiple-Emitter Super-resolution Imaging using the Alternating Descent Conditional Gradient Method

   Kandidat-uppsats, Lunds universitet/Beräkningsbiologi och biologisk fysik - Genomgår omorganisation; Lunds universitet/Institutionen för astronomi och teoretisk fysik - Genomgår omorganisation

   Författare :Dolev Illouz; [2023]
   Nyckelord :super-resolution; alternating descent conditional gradient method; ADCG; multiple-emitter localization; nanoscale imaging; single molecule tracking; Physics and Astronomy;

   Sammanfattning : This thesis examines the state-of-the-art 2D super-resolution technique alternating descent conditional gradient (ADCG) method's ability to accurately localize fluorophores in diffraction-limited single molecule images (SMI) and analyze the impact of pre-processing and post-processing modules on ADCG's fluorophore localization. A synthetic dataset obtained from the 2013 Grand Challenge localization microscopy and a temporally linked dataset obtained from an unpublished set of Optical DNA mapping experiments performed by Jonathan Jeffet at the NanoBioPhotonix Lab at Tel-Aviv University were initially segmented to extract their noise parameters. LÄS MER

7. 5. Simulating metal ct artefacts for ground truth generation in deep learning.

   Master-uppsats, Lunds universitet/Avdelningen för Biomedicinsk teknik

   Författare :Arthur Barakat; [2023]
   Nyckelord :Technology and Engineering;

   Sammanfattning : CT scanning stands as one of the most employed imaging techniques used in clinical field. In the presence of metal implants in the field of view (FOV), distortions and noise appear on the 3D image leading to inaccurate bone segmentation, often required for surgery planning or implant design. LÄS MER