Human in the Loop for AI-Based Anomaly Detection
Our new Feedback Loop feature enables continuous improvement of AI-based anomaly detection through targeted user annotations and intelligent prioritization of uncertain cases. In this way, we combine human expertise [...]
AI development with synthetic images for visual inspection of injection molded parts
Advances in the field of artificial intelligence (AI) are also opening up new opportunities for automation in visual quality inspection. However, a large amount of data is required to [...]
Tutorials – Anomaly Detection with the preML Dashboard
This article compiles the latest tutorials for the preML Dashboard. The dashboard includes various functionalities such as managing image datasets, training AI models, and displaying live systems. [...]
Consensus – How To Detect Data Poisoning with Active Learning
Active Learning is primarily about reducing the amount of data required to train an AI model. To do this, an AI model is used to specifically select the data [...]
How to create a high-quality data set for anomaly detection?
A major advantage of anomaly detection models is that they are trained exclusively with images that represent the ideal appearance of an object. This means that only images of [...]
News – preML one of the Top 20 Vision Tech Startups in 2024
We are nominated as one of the Top 20 Vision Tech Startups 2024! Now its your choice to select the winner! Just write a E-Mail with "𝐩𝐫𝐞𝐌𝐋 𝐆𝐦𝐛𝐇" to [...]