◆Sample program available & technical information published◆ Verified whether images collected outside the operating environment can be distinguished as training data.

We verified whether it is possible to distinguish images that were not taken in an actual operating environment using data learned from images captured with a smartphone camera!
For details, please see the URL below or related links.
https://qiita.com/shimamotosan/items/1a0c6c73b1e60ae5db43
■ What is DOBOT Magician?
Despite being in the price range of around 150,000 yen, it is a small robotic arm equipped with a 4-axis arm and comes with standard tool heads such as a gripper, suction cup kit, lighting & drawing, and 3D printer. The dedicated software allows programming by arranging blocks, enabling beginners to smoothly learn and operate the robotic arm. The main unit does not require prior safety education, making it less restricted in terms of installation and usage locations, and it can be utilized in various scenes. Afrel provides original guides (control learning texts) using dedicated software (DobotStudio) and programming languages to support the use of the robotic arm.
【DOBOT Magician explanatory article】
https://learninglab.afrel.co.jp/1074/

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This is the introduction page for DOBOT Magician.
We introduce case studies of robot arm applications.
When collecting learning data for target objects to be recognized in a sorting environment, AI image recognition may sometimes include image data collected outside of the actual operating environment.
In this case, we verified whether it is possible to recognize objects using image data taken with a smartphone camera that is not from the actual operating environment.
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