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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.
Autonomous vehicles need to detect and track other traffic participants, and that can be achieved by collecting various data of cars, trucks, buses, and motorcycles. After the data is collected, it has to be annotated and used to train a model.
Traffic Signs are an indispensable part of traffic, and since there are a lot of different ones, from different countries or regions, the most important thing is to collect enough data to make a model responsive and reliable in all situations.