The phrase "amount of data processed" is correct and usable in written English.
It can be used when discussing the quantity of data that has been handled or analyzed in a particular context, such as computing or data analysis.
Example: "The system can handle a significant amount of data processed in real-time, ensuring efficient performance."
Alternatives: "volume of data handled" or "quantity of data analyzed".
Similarly to most pattern detection methods in signal processing, the amount of data processed is reduced by first extracting candidate waveforms based on low-level detection analysis (by feature extraction), while subsequently classification is performed to maximize specificity of the overall method [3].
The experimental evaluation using a real-world table scene shows that while solving the given task, the amount of data processed and stored by our system is considerably lower compared to processing regimes used in state-of-the-art systems.
By evaluating a proof-of-concept implementation on a real-world table scene, we show that, while solving the given task, the amount of data processed and stored by the system is considerably lower compared to processing regimes used in state-of-the-art systems.
However, high-resolution and dynamic image reconstruction is computationally demanding because of the large amount of data processed.
The problem: Storage issues were created by the huge amount of data processed by the Google File System, (GFS), designed for Google web searches.
The quantitative evaluation considers image-processing applications and shows that the maximum performance depends on the amount of data processed by the reconfigurable hardware.
Stan also gathered a huge amount of Twitter data, processed it using Pig scripts, and graphed the results using Gephi.
The DHI, a non-profit consulting firm chartered by the Danish Government, has developed proprietary software capacity that can assimilate massive amounts of data, process and visualize it, and make it adaptable for testing impacts of projected future conditions and scenarios.
While it wasn't Intel and Hewlett-Packard infrastructure crunching the data, the amount of information processed to get the job done was massive.
This huge amount of data is processed on more than 140 computing centers distributed across 34 countries.
