Essays about: "potential segment"
Showing result 1 - 5 of 196 essays containing the words potential segment.
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1. Nested Noun Phrase Detection in English Text with BERT
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In this project, we address the task of nested noun phrase identification in English sentences, where a phrase is defined as a group of words functioning as one unit in a sentence. Prior research has extensively explored the identification of various phrases for language understanding and text generation tasks. READ MORE
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2. Double Machine Learning for Insurance Price Optimization
University essay from KTH/Skolan för industriell teknik och management (ITM)Abstract : This thesis examines how recent advances in debaised machine learning can be used for estimating price elasticities of demand within the automotive insurance field. Traditional methods such as generalized linear model (GLM) to estimate demand has no way of ensuring there are no biases in the underlying data selection, especially when the confounding variables are many. READ MORE
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3. Objective measurement of video quality
University essay from Uppsala universitet/Avdelningen Vi3Abstract : Automatic video quality assessment has many potential use cases in today’s video-filledsociety, for example, when trying to find highlights in a video. This thesis studies the possibilityof extracting the best segments from a video automatically based on five selected metrics:sharpness, colorfulness, contrast, stability, and aesthetics. READ MORE
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4. Developing an Automated Drivability Index for Swedish Roadways
University essay from KTH/TransportplaneringAbstract : The masters thesis aims to determine a method to understand which road segments could pose safety risks or where Level 4 autonomous vehicles would operate poorly in the Swedish road context. This vehicle’s ability to operate adequately can be defined as ‘drivable’. READ MORE
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5. Finding the QRS Complex in a Sampled ECG Signal Using AI Methods
University essay from KTH/FysikAbstract : This study aimed to explore the application of artificial intelligence (AI) and machine learning (ML) techniques in implementing a QRS detector forambulatory electrocardiography (ECG) monitoring devices. Three ML models, namely long short-term memory (LSTM), convolutional neural network (CNN), and multilayer perceptron (MLP), were compared and evaluated using the MIT-BIH arrhythmia database (MITDB) and the MIT-BIH noise stress test database (NSTDB). READ MORE