Sökning: "training methods and training models"

Visar resultat 1 - 5 av 435 uppsatser innehållade orden training methods and training models.

1. 1. Predictive Modeling of Pipetting Dynamics. Multivariate Regression Analysis: PLS and ANN for Estimating Density and Volume from Pressure Recordings

   Master-uppsats, Lunds universitet/Avdelningen för Biomedicinsk teknik

   Författare :Lisa Linard Pedersen; [2024]
   Nyckelord :Technology and Engineering;

   Sammanfattning : Thermo Fisher Scientific manufacture automatic pipetting instruments for diagnostic tests. These tests are sensitive to abnormalities and changes in e.g. volume or density could potentially lead to less precision or other issues in the pipetting work flow. LÄS MER

3. 2. Variational AutoEncoders and Differential Privacy : balancing data synthesis and privacy constraints

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Baptiste Bremond; [2024]
   Nyckelord :TVAE; Differential privacy; Tabular data; Synthetic data; DP-SGD; TVAE; differentiell integritet; tabelldata; syntetiska data; DP-SGD;

   Sammanfattning : This thesis investigates the effectiveness of Tabular Variational Auto Encoders (TVAEs) in generating high-quality synthetic tabular data and assesses their compliance with differential privacy principles. The study shows that while TVAEs are better than VAEs at generating synthetic data that faithfully reproduces the distribution of real data as measured by the Synthetic Data Vault (SDV) metrics, the latter does not guarantee that the synthetic data is up to the task in practical industrial applications. LÄS MER

4. 3. 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

5. 4. Designprocessen och maskininlärning: Framtiden för användarcentrerad design

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

   Författare :Lisa Marie Karin Gärdhammar; [2024]
   Nyckelord :Artificial Intelligence; Machine Learning; Design process; Journey Mapping; Empathy; User experience; Customer experience; Artificiell intelligens; Maskininlärning; Designprocessen; Journey Mapping; Empati; Användarupplevelse; Kundupplevelse;

   Sammanfattning : Artificiell intelligens (AI) och i synnerhet maskininlärning (ML) har inom UX-design visat potential att förbättra designprocessen genom att exempelvis identifiera användargrupper från stora datamängder, effektivisera idégenerering och automatisera repetitiva uppgifter. Det råder dock oenighet kring hur tekniken kan integreras i designprocessen. LÄS MER

7. 5. Classifying femur fractures using federated learning

   Master-uppsats, Linköpings universitet/Statistik och maskininlärning

   Författare :Hong Zhang; [2024]
   Nyckelord :Atypical femur fracture; Federated Learning; Neural Network; Classification;

   Sammanfattning : The rarity and subtle radiographic features of atypical femoral fractures (AFF) make it difficult to distinguish radiologically from normal femoral fractures (NFF). Compared with NFF, AFF has subtle radiological features and is associated with the long-term use of bisphosphonates for the treatment of osteoporosis. LÄS MER