
The increasing amount of video data generated requires efficient processing methods. Parallel stream processing can be implemented to handle large volumes of data, enabling fast results and improved performance. This approach can be particularly useful in video analysis applications, where timely processing is crucial. By leveraging parallel processing, video data can be efficiently analyzed, and insights can be gained quickly, leading to better decision-making and improved outcomes.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
