Your English writing platform
Discover LudwigSuggestions(5)
Exact(6)
The proposed model is tested against the recently released SENSIAC ATR database and the experimental results validate its efficacy both qualitatively and quantitatively.
Thirdly, the evaluation experiments are performed on the established iris database, and the experimental results suggest that the system shows good performance both on accuracy and efficiency.
We test our method on the Berkeley segmentation database, and the experimental results demonstrate that the proposed method is very effective in automatic image segmentation.
The p-value indicates the significance of the overlap between the genes targeted by the upstream regulator in the IPKB database and the experimental dataset.
Next, we cross-searched those potential identifications against our CCS lipid database, applying ΔCCS <3% as the difference between reference CCS values in our database and the experimental CCS values.
The p-value of overlap associated for each upstream regulator indicates the significance of the overlap between the genes targeted by the upstream regulator in the IPKB database and the experimental dataset.
Similar(54)
In this section, we first introduce the databases and the experimental setup.
Our method is verified on two challenging IQA databases, and the experimental results demonstrate that the proposed GMVP achieves higher prediction accuracy than that of previous methods on image quality assessment.
The proposed OD segmentation method is evaluated on three public available databases, i.e., the MESSIDOR, ONHSD and DRIONS databases, and the experimental results demonstrate that the proposed method outperforms the state-of-the art techniques.
Evaluation on several face databases and the experimental results demonstrate that these proposed classifiers can achieve greater performance than the C-PtP based 1-NNs and competitive recognition accuracy and robustness compared with the state-of-the-art classifiers.
In these experiments, we calculated the ΔCCS (the difference between the database CCS and the experimental CCS) and used this as a contribution to the identification score in addition to retention time and accurate mass.
More suggestions(2)
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com