1. Deep Learning for Computer Vision in the Manufacturing Industry – Insights from Johnson & Johnson (Vaibhav Verdhan)

Deep learning and Computer Vision are changing the way defects can be identified in manufacturing industry. Johnson and Johnson has used cutting edge neural network architectures to identify the source of problems in products. It improves the product quality and enhances the customer experience. The models are deployed into production and are generating fantastic results. It will be surely a great attraction for the visitors who want to analyse the significance of deep learning, identify the process and challenges. It will be a first hand information for them which will prove to be really useful and will have far-reaching results.

2. Bringing Research to Production: Modular and Highly Adjustable Computer Vision Pipelines (Thomas Wollmann)

Robust detection, segmentation, and classification of objects are crucial for computer vision applications in production. However, the challenges in real world use cases slow down fast adoption of new research findings. Academical efforts are seldom mature enough and ignore the context beyond a proof of concept. In this talk, Thomas presents how SemiAutoML and their modular and highly adjustable computer vision pipelines accelerate bringing research to production and solve real world use cases.

3. Generative Deep Learning for Image Anomaly Detection (Luca Marchesotti)

Supply chains are becoming extraordinarily efficient with the help of sophisticated machinery. These systems are designed to perform repetitive tasks with near-zero efficiency loss, but they are still unable to deal with rare and potentially harmful situations – long-tail events. In this talk, we will discuss how you can set up a fault detection system in your supply chain leveraging computer vision solutions to drastically boost your quality control performance.