Anomaly detection for industrial parts using PatchCore

• المؤلف الرئيسي: Kuah, Zheng Xuan
• مؤلفون آخرون: Yeo Chai Kiat
• التنسيق: Final Year Project
• اللغة: English
• منشور في: Nanyang Technological University 2022
• الموضوعات: Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/162909
• المؤسسة: Nanyang Technological University

The ability to detect imperfect parts is essential for components in a large-scale industrial manufacturing. The decision of an anomaly detection revolves around a binary problem. This paper will delve into a state-of-the-art method of anomaly detection known as PatchCore and its effectiveness...