The phrase "achieved impressive performance" is correct and usable in written English.
You can use it to describe someone or something that has reached a high level of success or effectiveness in a particular area or task.
Example: "The athlete achieved impressive performance during the championship, breaking several records."
Alternatives: "attained remarkable results" or "reached outstanding performance."
State-of-the-art methods have recently achieved impressive performance for recognising the objects present in large databases of pre-collected images.
Numerous dimensionality reduction methods have achieved impressive performance in face recognition field due to their potential to exploit the intrinsic structure of images and to enhance the computational efficiency.
Wright et al. [4] recently proposed the sparse representation based classification (SRC) scheme for face recognition which achieved impressive performance.
Fortunately, representation learning [25, 26], a promising solution to learn the meaningful and useful representations of the data that make it easier to extract useful information when building classifiers or other predictors, has been presented and achieved impressive performance on many dimensionality reduction tasks [27].
Table 2 summarizes the findings from task 2. Notably, both teams achieved impressive performance levels.
Recently, a number of edge-preserving filters like weighted least squares (WLS) [24] have been proposed to alleviate this drawback and achieved impressive performances.
Currently, with the data-driven approaches attracting wide attention, deep learning achieves impressive performance in semantic processing tasks without much effort on costly features.
Our results demonstrate that the LPLNS model based on the known disease-miRNA associations could achieve impressive performance with an AUC of 0.9034.
Compared to the two cognitive TCPs, the TCP-ACC achieves impressive performance, more than four times of conventional end-to-end TCP variants and more than double of TCPs specialized for the CMNs.
For example, in terms of high-dimensional datasets, representation learning seems to be a promising solution, which can learn the meaningful representations of the data that make it easier to extract useful information for achieving impressive performance on many dimensionality reduction tasks.
All these methods have achieved impressive classification performances.
