Essays about: "träning"

Showing result 1 - 5 of 639 essays containing the word träning.

  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. Examining the Possibilities of Live, Virtual, Constructive (LVC)

    University essay from Försvarshögskolan

    Author : Josefine Thunström; [2024]
    Keywords : LVC; train like you fight; test and analysis; radar; Military Utility; LVC; train like you fight; test och analys; radar; militär nytta;

    Abstract : Live, Virtual, and Constructive (LVC) is a relatively newly developed system of systems concept designed to provide a new way of conducting training for, but not exclusively, fighter pilots. “Train like you fight” is a commonly used quote when talking about LVC. READ MORE

  4. 3. Utilizing energy-saving techniques to reduce energy and memory consumption when training machine learning models : Sustainable Machine Learning

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

    Author : Khalid El Yaacoub; [2024]
    Keywords : Sustainable AI; Machine learning; Quantization-Aware Training; Model Distillation; Quantized Distillation; Siamese Neural Networks; Continual Learning; Experience Replay; Data Efficient AI; Energy Consumption; Energy-Savings; Sustainable ML; Computation resources; Hållbar maskin inlärning; Hållbar AI; Maskininlärning; Quantization-Aware Training; Model Distillation; Quantized Distillation; siamesiska neurala nätverk; Continual Learning; Experience Replay; Dataeffektiv AI; Energiförbrukning; Energibesparingar; Beräkningsresurser;

    Abstract : Emerging machine learning (ML) techniques are showing great potential in prediction performance. However, research and development is often conducted in an environment with extensive computational resources and blinded by prediction performance. READ MORE

  5. 4. Fysiologiskt svar under terrängmomentet i fälttävlan : pilotstudie under svenska förhållanden

    University essay from SLU/Dept. of Anatomy, Physiology and Biochemistry

    Author : Fanny Hansson; [2023]
    Keywords : Terrängträning; Fysiologiskt ansträngning; Hjärtfrekvens; Laktat;

    Abstract : I tävlingsgrenen fälttävlan är terrängdelen det som bedöms som mest fysiologiskt ansträngande för hästarna. Syftet med denna undersökning är att ta reda på det fysiologiska svaret under en träning på terrängmomentet i fälttävlan. READ MORE

  6. 5. EMONAS : Evolutionary Multi-objective Neuron Architecture Search of Deep Neural Network

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

    Author : Jiayi Feng; [2023]
    Keywords : DNN Deep Neural Network ; NAS Neural Architecture Search ; EA Evolutionary Algorithm ; Multi-Objective Optimization; Binary One Optimization; Embedded Systems; DNN Deep Neural Network ; NAS Neural Architecture Search ; EA Evolutionary Algorithm ; Multi-Objective Optimization; Binary One Optimization; Inbyggda system;

    Abstract : Customized Deep Neural Network (DNN) accelerators have been increasingly popular in various applications, from autonomous driving and natural language processing to healthcare and finance, etc. However, deploying them directly on embedded system peripherals within real-time operating systems (RTOS) is not easy due to the paradox of the complexity of DNNs and the simplicity of embedded system devices. READ MORE