Sökning: "deep learning"
Visar resultat 11 - 15 av 2058 uppsatser innehållade orden deep learning.
11. 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
12. Dynamik och tillförlighet i finansiell prognostisering : En analys av djupinlärningsmodeller och deras reaktion på marknadsmanipulation
M1-uppsats, KTH/Hälsoinformatik och logistikSammanfattning : Under åren har intensiv forskning pågått för att förbättra maskininlärningsmodellers förmåga att förutse marknadsrörelser. Trots detta har det, under finanshistorien, inträffat flera händelser, såsom "Flash-crash", som har påverkat marknaden och haft dramatiska konsekvenser för prisrörelserna. LÄS MER
13. Data Augmentation for Object Detection using Deep Reinforcement Learning
Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknikSammanfattning : Data augmentation is a concept which is used to improve machine learning models for computer vision tasks. It is usually done by firstly, defining a set of functions which transforms images and secondly, applying a random selection of these functions on the images. LÄS MER
14. Uncertainty Quantification in Deep Learning for Breast Cancer Classification in Point-of-Care Ultrasound Imaging
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : Breast cancer is the most common type of cancer worldwide with an estimate of 2.3 million new cases in 2020, and the number one cause of cancer-related deaths in women. LÄS MER
15. Exploring the Depth-Performance Trade-Off : Applying Torch Pruning to YOLOv8 Models for Semantic Segmentation Tasks
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In order to comprehend the environments from different aspects, a large variety of computer vision methods are developed to detect objects, classify objects or even segment them semantically. Semantic segmentation is growing in significance due to its broad applications in fields such as robotics, environmental understanding for virtual or augmented reality, and autonomous driving. LÄS MER