Sökning: "Reliable Machine Learning"

Visar resultat 1 - 5 av 192 uppsatser innehållade orden Reliable Machine Learning.

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

   Master-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

   Författare :Alexander Florean; [2024]
   Nyckelord :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;

   Sammanfattning : 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. LÄS MER

3. 2. Predicting inflow and infiltration to wastewater networks based on temperature measurements

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Martin Åsell; [2024]
   Nyckelord :Inflow and Infiltration; I I; CNN; Linear regression;

   Sammanfattning : Sewer pipelines are deteriorating due to aging and sub optimal material selections, leading to the infiltration of clean ground and rainfall water into the pipes. It is estimated that a significant portion (up to 40-50%) of the water entering wastewater treatment plants is actually clean infiltrated water. LÄS MER

4. 3. Physical Exercise and Fatigue Detection using Machine Learning

   Uppsats för yrkesexamina på grundnivå, Högskolan i Halmstad/Akademin för informationsteknologi

   Författare :Filip Säterberg; Rasmus Nilsson; [2024]
   Nyckelord :Machine Learning; Fatigue Prediction; Data Collection; Supervised learning; Surface Electromyography; Accelerometers; Maskininlärning; Trötthetsförutsägelse; Datainsamling; Övervakad; Ytlig-elektromyografi Accelerometrar;

   Sammanfattning : Monitoring of physical exercise is an important task to evaluate and adapt exercise to provide better exercise results. The Inno-X™ device, developed by Innowearable, is a device that can be used for such monitoring. It collects data using an accelerometer and sEMG sensor. LÄS MER

5. 4. Data Augmentation: Enhancing Named Entity Recognition Performance on Swedish Medical Texts

   Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :Lucas Rosvall; Niklas Paasonen; [2023-10-05]
   Nyckelord :Machine Learning; Information Extraction; Named Entity Recognition; BERT; Data Augmentation;

   Sammanfattning : Named Entity Recognition (NER) refers to the task of locating relevant information within text sequences. Within the medical domain, it can benefit applications such as de-identifying patient records or extracting valuable data for other downstream tasks. LÄS MER

7. 5. IDENTIFICATION OF ENVIRONMENTALLY RELEVANT BENTHIC FORAMINIFERA FROM THE SKAGERRAK FJORDS BY DEEP LEARNING IMAGE MODELING

   Master-uppsats, Göteborgs universitet / Institutionen för biologi och miljövetenskap

   Författare :Marko Plavetic; [2023-06-26]
   Nyckelord :benthic foraminifera; deep learning; environmental monitoring; YOLOv7;

   Sammanfattning : Over the several past decades, there has been increasing interest in using foraminifera as environmental indicators for coastal marine environments. As compared to macrofauna, which are currently used in environmental studies, foraminifera offer several distinct advantages as bioindicators, including short generation times, a high number of individuals per small sample volume, hard and durable tests with high preservation potential, and low cost of sample extraction. LÄS MER