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Visar resultat 1 - 5 av 2137 uppsatser som matchar ovanstående sökkriterier.

1. 1. Optimizing Flight Ranking:A Machine Learning Approach : Applying Machine Learning to Upgrade Flight Sorting and User Experience

   M1-uppsats, KTH/Hälsoinformatik och logistik

   Författare :Habib Jabeli; [2024]
   Nyckelord :Machine Learning; Flight Comparison; Flygresor.se; Neural Networks; Flight Ranking; Random Forest; XGBoost;

   Sammanfattning : 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

3. 2. Optical Communication using Nanowires and Molecular Memory Systems

   Master-uppsats, Lunds universitet/Fysiska institutionen; Lunds universitet/Synkrotronljusfysik

   Författare :Thomas Kjellberg Jensen; [2024]
   Nyckelord :neuromorphic computing; nanowire; molecular dye; DASA photoswitch; OBIC; Physics and Astronomy;

   Sammanfattning : 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. 3. Predicting Electricity Consumption with ARIMA and Recurrent Neural Networks

   Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

   Författare :Klara Enerud; [2024]
   Nyckelord :time series forecasting; ARIMA; recurrent neural networks; LSTM; electricity forecasting; EED forecasting;

   Sammanfattning : Due to the growing share of renewable energy in countries' power systems, the need for precise forecasting of electricity consumption will increase. This paper considers two different approaches to time series forecasting, autoregressive moving average (ARMA) models and recurrent neural networks (RNNs). LÄS MER

5. 4. A Comparative Analysis of Whisper and VoxRex on Swedish Speech Data

   Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

   Författare :Max Fredriksson; Elise Ramsay Veljanovska; [2024]
   Nyckelord :ASR; Automatic Speech Recognition; Swedish Speech Recognition; Speech Recognition Models; Speech-to-Text; Whisper; VoxRex; Wav2Vec; Model Comparison; Transformer Models; Neural Networks; Machine Learning; WER; Word Error Rate; Transcription;

   Sammanfattning : With the constant development of more advanced speech recognition models, the need to determine which models are better in specific areas and for specific purposes becomes increasingly crucial. Even more so for low-resource languages such as Swedish, dependent on the progress of models for the large international languages. LÄS MER

7. 5. AI-based image generation: The impact of fine-tuning on fake image detection

   Kandidat-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

   Författare :Nick Hagström; Anders Rydberg; [2024]
   Nyckelord :Fake image detection; LoRA; DreamBooth; Stable Diffusion; Image generation;

   Sammanfattning : Machine learning-based image generation models such as Stable Diffusion are now capable of generating synthetic images that are difficult to distinguish from real images, which gives rise to a number of legal and ethical concerns. As a potential measure of mitigation, it is possible to train neural networks to detect the digital artifacts present in the images synthesized by many generative models. LÄS MER