Sökning: "art learning processes"
Visar resultat 1 - 5 av 72 uppsatser innehållade orden art learning processes.
1. PVCFA: Principal Variation Context Feature Attribution : Distributed Chess for Perturbation-based Saliency Maps
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : The research and development field of computer chess improved more in the last 5 years than in the whole history of computers. Unfortunately these unprecedented results comes with techniques that don’t leave much space to intuition and comprehensibility for humans. LÄS MER
2. Deep Learning-Based Anomaly Detection for Predictive Maintenance of Cold Isostatic Press
Master-uppsats, Mälardalens universitet/Akademin för innovation, design och teknikSammanfattning : Predictive maintenance is an automated technique that analyses sensor data from industrial systems to enable downtime planning. Available for this study is unlabelled data from sensors placed in proximity to hydraulic system outlets of a cold isostatic press. LÄS MER
3. KARTAL: Web Application Vulnerability Hunting Using Large Language Models : Novel method for detecting logical vulnerabilities in web applications with finetuned Large Language Models
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Broken Access Control is the most serious web application security risk as published by Open Worldwide Application Security Project (OWASP). This category has highly complex vulnerabilities such as Broken Object Level Authorization (BOLA) and Exposure of Sensitive Information. LÄS MER
4. Meta-Pseudo Labelled Multi-View 3D Shape Recognition
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : The field of computer vision has long pursued the challenge of understanding the three-dimensional world. This endeavour is further fuelled by the increasing demand for technologies that rely on accurate perception of the 3D environment such as autonomous driving and augmented reality. LÄS MER
5. Evaluation of Ferroelectric Tunnel Junction memristor for in-memory computation in real world use cases
Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknikSammanfattning : Machine learning algorithms are experiencing unprecedented attention, but their inherent computational complexity leads to high energy consumption. However, a paradigm shift in computing methods has the potential to address the issue. LÄS MER