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Visar resultat 1 - 5 av 2313 uppsatser som matchar ovanstående sökkriterier.
1. Optimizing Flight Ranking:A Machine Learning Approach : Applying Machine Learning to Upgrade Flight Sorting and User Experience
M1-uppsats, KTH/Hälsoinformatik och logistikSammanfattning : Flygresor.se, a leading flight comparison platform, uses machine learning to rankflights based on their likelihood of being clicked. The main goal of this project was toimprove this flight sorting to obtain a better user experience. The platform's existingmodel is based on a neural network approach and a limited set of features. LÄS MER
2. Predictive Modeling of Pipetting Dynamics. Multivariate Regression Analysis: PLS and ANN for Estimating Density and Volume from Pressure Recordings
Master-uppsats, Lunds universitet/Avdelningen för Biomedicinsk teknikSammanfattning : Thermo Fisher Scientific manufacture automatic pipetting instruments for diagnostic tests. These tests are sensitive to abnormalities and changes in e.g. volume or density could potentially lead to less precision or other issues in the pipetting work flow. LÄS MER
3. Optical Communication using Nanowires and Molecular Memory Systems
Master-uppsats, Lunds universitet/Fysiska institutionen; Lunds universitet/SynkrotronljusfysikSammanfattning : Neuromorphic computational networks, inspired by biological neural networks, provide a possible way of lowering computational energy cost, while at the same time allowing for much more sophisticated devices capable of real-time inferences and learning. Since simulating artificial neural networks on conventional computers is particularly inefficient, the development of neuromorphic devices is strongly motivated as the reliance on AI-models increases. LÄS MER
4. Using NeRF- and Mesh-Based Methods to Improve Visualisation of Point Clouds
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : In recent years, the field of generating synthetic images from novel view points has seen some major improvements. Most importantly with the publication of Neural Radiance Fields allowing for extremely detailed and accurate 3D novel views. LÄS MER
5. Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods
Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapSammanfattning : Public Bike-Sharing systems have been employed in many cities around the globe. Shared bikes are an efficient and convenient means of transportation in advanced societies. Nonetheless, station planning and local bike-sharing network effectiveness can be challenging. LÄS MER