GitHub repository: qBraid/BMW_Challenge
Primary language: Jupyter Notebook
Created: 2021-09-21T03:02:16Z
Description:    Due to the rapid development of hardware and software, the past decades have drastically shifted quality control from manual examination towards automated inspection. In the light of the required human expertise to hand-tune algorithms, machine learning (ML) techniques promise a more general and scalable approach to quality control. The remarkable success of convolutional neural networks (CNNs) in image processing has revolutionized automated quality inspection. Of course, any technology has its limitation, and for CNNs, it is computation power. As high-performance CNNs usually assume large datasets, datacenters ultimately end up with large numerical workloads and expensive GPUs. Quantum computing may one day break through classical computational bottlenecks, providing faster and more efficient training with higher accuracy.