Automatic vs. manual labeling in offline perception: a balancing act for more precise results
In the world of offline perception, data plays a crucial role. The quality of perception algorithms depends heavily on how accurately and comprehensively the training data is labeled.
Although automatic labeling is often considered a faster and more cost-effective method, it often does not offer the necessary precision for complex applications. This is where manual approaches come into play: they offer the flexibility and accuracy to correctly capture even the smallest details in the data – a crucial factor for safety-critical applications.
The key lies in an intelligent combination of both methods. Automated labeling can process large amounts of data efficiently, while manual checks and fine adjustments ensure the necessary precision. At AVL Software and Functions GmbH, we maximize efficiency and quality of results with this hybrid approach.
Contact us for a demo at adas-perception@avl.com or leave a comment below this post.
We look forward to showing you how automatic and manual labeling can improve your perception solutions!
