Sökning: "real-world network data"

Visar resultat 1 - 5 av 186 uppsatser innehållade orden real-world network data.

1. 1. Attack Strategies in Federated Learning for Regression Models : A Comparative Analysis with Classification Models

   Master-uppsats, Umeå universitet/Institutionen för datavetenskap

   Författare :Sofia Leksell; [2024]
   Nyckelord :Federated Learning; Adversarial Attacks; Regression; Classification;

   Sammanfattning : Federated Learning (FL) has emerged as a promising approach for decentralized model training across multiple devices, while still preserving data privacy. Previous research has predominantly concentrated on classification tasks in FL settings, leaving  a noticeable gap in FL research specifically for regression models. LÄS MER

3. 2. Generative adversarial network for point cloud upsampling

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

   Författare :Edison Widell Delgado; [2024]
   Nyckelord :Point cloud upsampling; Generative adversarial network; GAN;

   Sammanfattning : Point clouds are a widely used system for the collection and application of 3D data. But most timesthe data gathered is too scarce to reliably be used in any application. LÄS MER

4. 3. Attack Strategies in Federated Learning for Regression Models : A Comparative Analysis with Classification Models

   Master-uppsats, Umeå universitet/Institutionen för tillämpad fysik och elektronik

   Författare :Sofia Leksell; [2024]
   Nyckelord :Federated Learning; Adversarial Attacks; Regression; Classification;

   Sammanfattning : Federated Learning (FL) has emerged as a promising approach for decentralized model training across multiple devices, while still preserving data privacy. Previous research has predominantly concentrated on classification tasks in FL settings, leaving  a noticeable gap in FL research specifically for regression models. LÄS MER

5. 4. Improvement of anautomatic networkdrawing algorithm in thecontext of utility networks

   Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

   Författare :Hyacinthe Ménard; [2024]
   Nyckelord :District Heating Network; Mathematical Optimization; Python; Fjärrvärme; Optimeringslära; Python;

   Sammanfattning : The European Union’s ambitious climate targets necessitate substantial reductions in greenhouse gas emissions, particularly within the heating and cooling sector, which accounts for a significant portion of energy consumption. District Heating and Cooling (DHC) systems emerge as a key solution for decarbonizing this sector by enabling high efficiency heat production and the integration of renewable and carbon-neutral energy sources. 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