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Our in-house professionals, using our image annotation tools with built-in machine learning and multiple layers of quality control, create the tightest and most accurately bounding boxes for computer vision and deep learning applications.
Each pixel in an image is mapped into specific classes; for example 'cars' and 'pedestrians' in autonomous driving data.
Every pixel in an image is mapped to specific classes. Regularly used in drone and autonomous driving technology.
Each frame or key-frames annotated with or without object tracking.
When it comes to large systems with many processes, it is difficult to devote time to each of them equally. Fruit picking can be time-consuming, but nowadays we have robots that can do the process very efficiently and without human help. If you want to train your robots perfectly, you need to collect real data and annotate it with appropriate taxonomy.
Automatically assess a forest's value by counting and analyzing every tree. Images can come from mobile phones, drones and even satellites. Combine trained machine learning models with forestry experts to achieve the most accurate valuations possible.