Traditionally, the data cleansing is defined as the process of detecting and correcting (or removing) corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the data and then replacing, modifying, or deleting the dirty or coarse data.
Accelerating Big Data Analysis with TTI’s Data Cleansing Strategy
Posted by
Dr. Fanqi Meng on Mar 1, 2023 7:11:23 PM
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Topics: Sensor Data, Sensor Data Management, data cleansing
What Will it Take for Fully Autonomous Vehicles to Become a Reality?
Posted by
Dr. Fanqi Meng on Dec 4, 2018 6:43:00 PM
Self-driving cars offer a safe, efficient and cost-effective solution that will dramatically redefine the future of human mobility.
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Topics: IIoT, Autonomous Vehicles, Sensor Data, Machine Learning, ADAS