Sökning: "Deep Learning"
Visar resultat 1 - 5 av 915 uppsatser innehållade orden Deep Learning.
1. Deep learning exotic derivatives
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för systemteknikSammanfattning : Monte Carlo methods in derivative pricing are computationally expensive, in particular for evaluating models partial derivatives with regard to inputs. This research proposes the use of deep learning to approximate such valuation models for highly exotic derivatives, using automatic differentiation to evaluate input sensitivities. LÄS MER
2. Group Invariant Convolutional Boltzmann Machines
Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaperSammanfattning : We investigate group invariance in unsupervised learning in the context of certain generative networks based on Boltzmann machines. Specifically, we introduce a generalization of restricted Boltzmann machines which is adapted to input data that is acted upon by any compact group G. LÄS MER
3. Convolutional neural networks for semantic segmentation of FIB-SEM volumetric image data
Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaperSammanfattning : Focused ion beam scanning electron microscopy (FIB-SEM) is a well-established microscopytechnique for 3D imaging of porous materials. We investigate three poroussamples of ethyl cellulose microporous films made from ethyl cellulose and hydroxypropylcellulose (EC/HPC) polymer blends. LÄS MER
4. Interactionwise Semantic Awareness in Visual Relationship Detection
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : Visual Relationship Detection (VRD) is a relatively young research area, where thegoal is to develop prediction models for detecting the relationships between objectsdepicted in an image. A relationship is modeled as a subject-predicate-object triplet,where the predicate (e.g an action, a spatial relation, etc. LÄS MER
5. Geo-temporal Online Analysis of Traffic Rule Violations
Kandidat-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : Due to inattention and not complying with traffic regulations, human error accounts forroughly 94% of all traffic accidents. To counter this, the need to develop systems that canidentify traffic rule violations and calculate the risk of collisions. The information reportedcan then be used to implement preventive measures. LÄS MER
