Fortifying Quality
Management with
Deep Learning

Why this use case matters

Deep learning, specifically computer vision and natural language processing, can be designed to identify defects during quality checks. These deep learning models can verify that products aren’t defective and labels/packaging present, correct, straight, and readable, saving huge amounts of repetitive work for increased process accuracy.

Techniques

Natural Language Processing, Computer Vision, Classification

Algorithms

Single-Shot Detection, YOLO, Mask-R CNN, Res-Net50, RanSaC, Filtering, Auto-Encoders, GPT-3, Transformers (RNNs), BERT, ERNIE, Word2vec

Outcome

Automating & improving human-based quality checks at scale.

Mosaic used deep learning to automate the work-intensive task of quality checking and rectifying information on product packaging.

Mosaic has compiled our industry expertise into a Machine Learning playbook for Manufacturing.