Essays about: "measure intelligence"

Showing result 1 - 5 of 61 essays containing the words measure intelligence.

  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. Mutual Enhancement of Environment Recognition and Semantic Segmentation in Indoor Environment

    University essay from

    Author : Venkata Vamsi Challa; [2024]
    Keywords : Semantic Segmentation; Scene Classification; Environment Recognition; Machine Learning; Deep Learning; Image Classification; Vision Transformers; SAM Segment Anything Model ; Image Segmentation; Contour-aware semantic segmentation;

    Abstract : Background:The dynamic field of computer vision and artificial intelligence has continually evolved, pushing the boundaries in areas like semantic segmentation andenvironmental recognition, pivotal for indoor scene analysis. This research investigates the integration of these two technologies, examining their synergy and implicayions for enhancing indoor scene understanding. READ MORE

  4. 3. Artificial Intelligence and its Implication for Future Jobs : Assessing The Bureau of Labor Statistics’ Adaptation to Artificial Intelligence in Projected Employment Figures in the United States

    University essay from Uppsala universitet/Nationalekonomiska institutionen

    Author : Aradhna Juwaheer; Dennis Dahlberg Barkholz; [2023]
    Keywords : Artificial Intelligence; Labor Market; Employment Forecasts; Labor Statistics; BLS; Occupational Outlook;

    Abstract : Artificial intelligence is often believed to have a detrimental effect on employment. However, when reviewing employment forecasts from The U.S. Bureau of Labor Statistics, no information could be found indicating whether they considered the potential impact of artificial intelligence on employment. READ MORE

  5. 4. Unsupervised Clustering of Behavior Data From a Parking Application : A Heuristic and Deep Learning Approach

    University essay from Umeå universitet/Institutionen för matematik och matematisk statistik

    Author : Edvard Magnell; Joakim Nordling; [2023]
    Keywords : ML; Machine learning; clustering; unsupervised learning; deep learning; autoencoder; AI; artificial intelligence;

    Abstract : This report aims to present a project in the field of unsupervised clustering on human behavior in a parking application. With increasing opportunities to collect and store data, the demands to utilize the data in meaningful ways also increase. READ MORE

  6. 5. Towards Building Privacy-Preserving Language Models: Challenges and Insights in Adapting PrivGAN for Generation of Synthetic Clinical Text

    University essay from Stockholms universitet/Institutionen för data- och systemvetenskap

    Author : Atena Nazem; [2023]
    Keywords : Generative Adversarial Networks; privacy-preserving language models; clinical text data; reinforcement learning; synthetic data;

    Abstract : The growing development of artificial intelligence (AI), particularly neural networks, is transforming applications of AI in healthcare, yet it raises significant privacy concerns due to potential data leakage. As neural networks memorise training data, they may inadvertently expose sensitive clinical data to privacy breaches, which can engender serious repercussions like identity theft, fraud, and harmful medical errors. READ MORE