The phrase "algorithm enhancements" is correct and usable in written English.
It can be used when discussing improvements or upgrades made to algorithms in various contexts, such as technology, data analysis, or software development.
Example: "The recent algorithm enhancements have significantly improved the accuracy of our predictive models."
Alternatives: "algorithm improvements" or "algorithm upgrades".
Future research will also focus on algorithm enhancements, OD demand calibration/validation, as well as valuating potential applications with other network design models.
And because Jumio's other product, the id verification system known as Netverify, also takes advantage of the same core technology, it too benefits from the algorithm enhancements here, as does the desktop version of Netswipe.
The usability of our algorithm in 'music education and practice' applications is addressed by considering efficiency and quality requirements in this context and proposing algorithm enhancements to meet such requirements.
However, an example of the impact of one algorithm enhancement on the performance of the software does warrant mention.
This work provides an assessment, and an algorithm enhancement when needed, of several existing techniques aimed to build an effective reduction basis for model order reduction.
Feature space transformation is widely applied to data visualization and learning algorithm enhancement.
For each sample, results were documented as cycle threshold (CT) set to 100 relative fluorescence unit values of background subtracted qPCR fluorescence kinetics by using the MX Pro Stratagene analysis software, applying the adaptive baseline, amplification based threshold and moving average algorithm enhancement.
For each sample, results were documented as cycle threshold (threshold set to 100 relative fluorescence units) values of background subtracted qPCR fluorescence kinetics by using the MX Pro Stratagene analysis software, applying the adaptive baseline, amplification based threshold, and moving average algorithm enhancement.
This paper proposes a surround suppression variational Retinex enhancement algorithm for image enhancement of non-uniform illumination images, which not only enhances the contrast of the image but also preserves the color constancy.
Most existing algorithms seek enhancements in product yield and growth rate, with the hopeful assumption that by improving these two attributes, titer and productivity will also improve.
Regarding the concerns of subjectivity and consistency of the manually generated borders, 5 6 many automatic border detection methods have been developed, such as the JSEG algorithm, contrast enhancement and clustering algorithms, with different evaluation metrics.
