Sökning: "deep learning approach"
Visar resultat 1 - 5 av 551 uppsatser innehållade orden deep learning approach.
1. Attack Strategies in Federated Learning for Regression Models : A Comparative Analysis with Classification Models
Master-uppsats, Umeå universitet/Institutionen för datavetenskapSammanfattning : 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
2. Evaluation of Deep Q-Learning Applied to City Environment Autonomous Driving
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Signaler och systemSammanfattning : This project’s goal was to assess both the challenges of implementing the Deep Q-Learning algorithm to create an autonomous car in the CARLA simulator, and the driving performance of the resulting model. An agent was trained to follow waypoints based on two main approaches. LÄS MER
3. Self-Supervised Learning for Tabular Data: Analysing VIME and introducing Mix Encoder
Kandidat-uppsats, Lunds universitet/Fysiska institutionenSammanfattning : We introduce Mix Encoder, a novel self-supervised learning framework for deep tabular data models based on Mixup [1]. Mix Encoder uses linear interpolations of samples with associated pretext tasks to form useful pre-trained representations. LÄS MER
4. Attack Strategies in Federated Learning for Regression Models : A Comparative Analysis with Classification Models
Master-uppsats, Umeå universitet/Institutionen för tillämpad fysik och elektronikSammanfattning : 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. Virtual H&E Staining Using PLS Microscopy and Neural Networks
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : Histopathological examination, crucial in diagnosing diseases such as cancer, traditionally relies on time- and resource-consuming, poorly standardized chemical staining for tissue visualization. This thesis presents a novel digital alternative using generative neural networks and a point light source (PLS) microscope to transform unstained skin tissue images into their stained counterparts. LÄS MER