Segmentation and object detection

Object recognition with neural networks enables automatic identification and localization of components, structures, or defects in image data.
Unlike traditional image processing, it is not based on rigid rules or thresholds. The neural network uses learned features that it has independently recognized during training.
This means that a model can not only detect individual objects, but also detect, count, or mark multiple components simultaneously with precise positioning – such as screws, solder joints, labels, or defective surfaces.