Sökning: "Classification Techniques"

Visar resultat 16 - 20 av 532 uppsatser innehållade orden Classification Techniques.

  1. 16. A requirements engineering approach in the development of an AI-based classification system for road markings in autonomous driving : a case study

    Master-uppsats, Blekinge Tekniska Högskola/Institutionen för programvaruteknik

    Författare :Srija Sunkara; [2023]
    Nyckelord :Requirements Engineering; Machine Learning; Goal-Oriented Requirements Engineering; Autonomous Driving; Point Cloud Classification;

    Sammanfattning : Background: Requirements engineering (RE) is the process of identifying, defining, documenting, and validating requirements. However, RE approaches are usually not applied to AI-based systems due to their ambiguity and is still a growing subject. LÄS MER

  3. 17. Predictive Modeling and Statistical Inference for CTA returns : A Hidden Markov Approach with Sparse Logistic Regression

    Master-uppsats, Umeå universitet/Institutionen för matematik och matematisk statistik

    Författare :Oskar Fransson; [2023]
    Nyckelord :Probability theory; Statistical inference; finance; CTA; managed futures; machine learning; statistical learning; stochastic process; sparse logistic regression; Markov Chain Monte Carlo; Hidden Markov model;

    Sammanfattning : This thesis focuses on predicting trends in Commodity Trading Advisors (CTAs), also known as trend-following hedge funds. The paper applies a Hidden Markov Model (HMM) for classifying trends. Additionally, by incorporating additional features, a regularized logistic regression model is used to enhance prediction capability. LÄS MER

  4. 18. Towards a feedback system for upper body bodyweight exercises using multiple inertial measurement units : A user-centred approach

    Master-uppsats, KTH/Medicinteknik och hälsosystem

    Författare :Panagiota Papadopoulou; [2023]
    Nyckelord :IMU sensors; bodyweight training; machine learning; real-time feedback; push-ups; tricep dips; plank;

    Sammanfattning : This thesis explores the feasibility of developing an affordable and easy-to-use feed- back system that leverages information from multiple inertial measurement units (IMUs) to identify mistakes during upper body bodyweight training and provide real-time feedback to the user. To develop the system, a human-centered approach was used, which involved conducting semi-structured interviews with movement ex- perts and a workshop with targeted end-users to understand their needs. LÄS MER

  5. 19. Exploring Advanced Clustering Techniques for Business Descriptions : A Comparative Study and Analysis of DBSCAN, K-Means, and Hierarchical Clustering

    Uppsats för yrkesexamina på avancerad nivå, Mittuniversitetet/Institutionen för data- och elektroteknik (2023-)

    Författare :Wisam Orabi Alkhen; [2023]
    Nyckelord :Machine learning; Business descriptions; Search scope reduction; Relevant business terminology; Data analysis.;

    Sammanfattning : In this study, we introduce several approaches to analyze large volumes of business descriptions by applying machine learning clustering and classification algorithms. The goal is to efficiently classify these descriptions, reducing the search scope and allowing for better business insights and decision-making processes. LÄS MER

  7. 20. Emphysema Classification via Deep Learning

    Master-uppsats, Umeå universitet/Institutionen för datavetenskap

    Författare :Olov Molin; [2023]
    Nyckelord :Deep learning; emphysema; CNN;

    Sammanfattning : Emphysema is an incurable lung airway disease and a hallmark of Chronic Obstructive Pulmonary Disease (COPD). In recent decades, Computed Tomography (CT) has been used as a powerful tool for the detection and quantification of different diseases, including emphysema. The use of CT comes with a potential risk: ionizing radiation. LÄS MER