Deep Learning for Autonomous Vehicle Sensor Error Correction
Keywords:
deep learning (DL)-based methodsAbstract
The typical strategy for SIM involves three steps, namely, generation of the erroneous data, sensor fault Accompanying it thus the data has shown better pictorial representations. The papers are written so that it defines the output from the camera and the lidar. The temporal error profits error directly from the previous error of the sensor. The papers are written existing strategies of motion are previously used by authors to prove the weakness on approach. By making the stepwise on the relevant data it gives the specific details of all the datasets. The error correction notes the groups of below three different options involved. The most common strategy is duplication and comparison of one kind and the other kind are probability calculation.
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References
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