Essays about: "Experiment Ramverk"

Showing result 1 - 5 of 65 essays containing the words Experiment Ramverk.

1. 1. Measuring the Utility of Synthetic Data : An Empirical Evaluation of Population Fidelity Measures as Indicators of Synthetic Data Utility in Classification Tasks

   University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

   Author : Alexander Florean; [2024]
   Keywords : Synthetic Data; Machine Learning; Population Fidelity Measures; Utility Metrics; Synthetic Data Quality Evaluation; Classification Algorithms; Utility Estimation; Data Privacy; Artificial Intelligence; Experiment Framework; Model Performance Assessment; Syntetisk Data; Maskininlärning; Population Fidelity Mätvärden; Användbarhetsmätvärden; Kvalitetsutvärdering av Syntetisk Data; Klassificeringsalgoritmer; Användbarhetsutvärdering; Dataintegritet; Artificiell Intelligens; AI; Experiment Ramverk; Utvärdering av Modellprestanda;

   Abstract : In the era of data-driven decision-making and innovation, synthetic data serves as a promising tool that bridges the need for vast datasets in machine learning (ML) and the imperative necessity of data privacy. By simulating real-world data while preserving privacy, synthetic data generators have become more prevalent instruments in AI and ML development. READ MORE

3. 2. A theoretical framework for interpretation and prediction of magneto-optical measurements

   University essay from Uppsala universitet/Materialteori

   Author : Viktor Frilén; [2023]
   Keywords : moke; tmoke; lmoke; pmoke; magneto-optical effects; layered media; dielectric function; maxwells equations; dielectric tensor; linear respons; magnetism; light induced transistions; DFT; SO;

   Abstract : The interplay of experiments and theory is essential to deepen our understanding of magnetization dynamics. This thesis aims to serve as a bridge between these two aspects by establishing a mathematical framework that enables the computation of optical observable quantities based on theoretical models. READ MORE

4. 3. Experiments with Visual Odometry for Hydrobatic Autonomous Underwater Vehicles

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Somnath Balaji Suresh Kumar; [2023]
   Keywords : Hydrobatic AUVs; VO; Stonefish; ORB-SLAM2; VISO2; Hydrobatiska AUV:er; VO; Stonefish; ORB-SLAM2; VISO2;

   Abstract : Hydrobatic Autonomous Underwater Vehicles (AUVs) are underactuated robots that can perform agile maneuvers in challenging underwater environments with high efficiency in speed and range. The challenge lies in localizing and navigating these AUVs particularly for performing manipulation tasks because common sensors such as GPS become very unreliable underwater due to their poor accuracy. READ MORE

5. 4. AI/ML Development for RAN Applications : Deep Learning in Log Event Prediction

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Yuxin Sun; [2023]
   Keywords : LSTM; Anomaly Detection; Failure Prediction; Log Mining; Deep Learning; LSTM; Anomali Detection; Failure Prediction; Log Mining; Deep Learning;

   Abstract : Since many log tracing application and diagnostic commands are now available on nodes at base station, event log can easily be collected, parsed and structured for network performance analysis. In order to improve In Service Performance of customer network, a sequential machine learning model can be trained, test, and deployed on each node to learn from the past events to predict future crashes or a failure. READ MORE

6. 5. Language Models as Evaluators : A Novel Framework for Automatic Evaluation of News Article Summaries

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Celine Helgesson Hallström; [2023]
   Keywords : Natural Language Processing; Large Language Models; Automatic Text Evaluation; Text Summarization; Multilingualism; Naturlig Språkbehandling; Stora Språkmodeller; Automatisk Textutvärdering; Textsammanfattning; Flerspråkighet;

   Abstract : The advancements in abstractive summarization using Large Language Models (LLMs) have brought with it new challenges in evaluating the quality and faithfulness of generated summaries. This thesis explores a human-like automated method for evaluating news article summaries. READ MORE