Essays about: "Deep CNN"
Showing result 1 - 5 of 344 essays containing the words Deep CNN.
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1. Evaluation of Deep Q-Learning Applied to City Environment Autonomous Driving
University essay from Uppsala universitet/Signaler och systemAbstract : This project’s goal was to assess both the challenges of implementing the Deep Q-Learning algorithm to create an autonomous car in the CARLA simulator, and the driving performance of the resulting model. An agent was trained to follow waypoints based on two main approaches. READ MORE
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2. Leveraging CNN for Automated Peak Picking in Untargeted Metabolomics without Parameter Dependencies
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : Metabolomics is a scientific discipline that involves the thorough analysis of small molecules, known as metabolites, found within a biological system. Furthermore, liquid chromatography-mass spectrometry (LC-MS) is a commonly used analytical technique in metabolomics for analysing biological samples due to its broad coverage of the measurable metabolome. READ MORE
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3. CNN-LSTM architecture for predicting hazardous driving situations
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : This study aims to investigate how a CNN-LSTM model can be used together with recorded vehicle data from trucks and external weather data in order to predict a hazardous driving situation. The dataset consists of three-second-long driving snippets from customer and development trucks registered within Europe. READ MORE
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4. Implementations and evaluation of machine learning algorithms on a microcontroller unit for myoelectric prosthesis control
University essay from Lunds universitet/Avdelningen för Biomedicinsk teknikAbstract : Using a microcontroller unit to implement different machine learning algorithms for myoelectric prosthesis control is currently feasible. Still there are hardware and timing constraints that need to be accounted for. READ MORE
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5. Neural Network-based Anomaly Detection Models and Interpretability Methods for Multivariate Time Series Data
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : Anomaly detection plays a crucial role in various domains, such as transportation, cybersecurity, and industrial monitoring, where the timely identification of unusual patterns or outliers is of utmost importance. Traditional statistical techniques have limitations in handling complex and highdimensional data, which motivates the use of deep learning approaches. READ MORE