Sökning: "Deep learning"
Visar resultat 1 - 5 av 1002 uppsatser innehållade orden Deep learning.
- Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik
Sammanfattning : The Autonomous Drive (AD) systems and Advanced Driver Assistance Systems(ADAS) in the current and future generations of vehicles include a large numberof sensors which are used to perceive the vehicle’s surroundings. The productionsensors of these vehicles are verified and validated against reference data that areoriginated from high-accurate reference sensors that are placed in a reference roofbox at the top of the vehicle. LÄS MER
- Kandidat-uppsats, Göteborgs universitet/Institutionen för nationalekonomi med statistik
Sammanfattning : In this thesis we aim to provide a fully data driven approach for modelling financial derivatives, exclusively using deep learning. In order for a derivatives model to be plausible, it should adhere to the principle of no-arbitrage which has profound consequences on both pricing and risk management. LÄS MER
- Master-uppsats, KTH/Optimeringslära och systemteori
Sammanfattning : Segmentation of magnetic resonance images is an important part of planning radiotherapy treat-ments for patients with brain tumours but due to the number of images contained within a scan and the level of detail required, manual segmentation is a time consuming task. Convolutional neural networks have been proposed as tools for automated segmentation and shown promising results. LÄS MER
- Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)
Sammanfattning : The information era has led the manufacturer of trucks and logistics solution providers are inclined towards software as a service (SAAS) based solutions. With advancements in software technologies like artificial intelligence and deep learning, the domain of computer vision has achieved significant performance boosts that it competes with hardware based solutions. LÄS MER
5. Image-to-Image Translation for Improvement of Synthetic Thermal Infrared Training Data Using Generative Adversarial NetworksMaster-uppsats, Linköpings universitet/Datorseende
Sammanfattning : Training data is an essential ingredient within supervised learning, yet time con-suming, expensive and for some applications impossible to retrieve. Thus it isof interest to use synthetic training data. However, the domain shift of syntheticdata makes it challenging to obtain good results when used as training data fordeep learning models. LÄS MER