Sökning: "Deep Learning"
Visar resultat 1 - 5 av 1056 uppsatser innehållade orden Deep Learning.
- Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaper
Sammanfattning : AbstractSoftware development with continuous integration changes needs frequent testing forassessment. Analyzing the test output manually is time-consuming and automatingthis process could be beneficial to an organization. LÄS MER
- 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
4. Detecting Slag Formation with Deep Learning Methods : An experimental study of different deep learning image segmentation modelsMaster-uppsats, Linköpings universitet/Datorseende
Sammanfattning : Image segmentation through neural networks and deep learning have, in the recent decade, become a successful tool for automated decision-making. For Luossavaara-Kiirunavaara Aktiebolag (LKAB), this means identifying the amount of slag inside a furnace through computer vision. 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