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1. Examples of ground truth It takes a thousand words to describe a concept, so it is better to give a few examples to make it clear. The following is the ground truth in several classic tasks. 1. Image classification Image classification is a task in the field of machine learning, and its goal is to classify input. Is it even possible or do i have to do it some other way besid. Kitti dataset contains task of visual odometry and you can download the ground truth poses that provided for the sequences of the specific task.

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Ground truth is a real annotation box, that is, a manual annotation. It is generally regarded as a "true value". It is generally believed that (why it is generally believed, please refer to the content in the last parentheses of the following paragraph) is the final prediction result of the network, which is "possible." For semantic segmentation every pixel of an image should be labeled. I want to combine imu data.

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