List of the time used by each algorithm. by JiaMing Gong (20427837)

“…Finally, to solve the issue of concept drift, EDAC designs and implements an ensemble classifier that uses a self-feedback strategy to determine the initial weight of the classifier by adjusting the weight of the sub-classifier according to the performance on the arrived data chunks. …”

Algorithm for optimizing the model using transformer. by Weiling Liu (1465480)

The data used in the figures. by Yonghui Zhang (279832)

Subjects:

The algorithm of the applied models. by Elif Tuçe Bal (21367965)

Subjects:

Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

Comparisons of the measured and simulated data of phenological stages (day of year) using the different algorithms, calibration data, and evaluation data. by Yonghui Zhang (279832)

Subjects:

The framework of the three algorithms for estimating crop model parameters in this work. by Yonghui Zhang (279832)

Subjects:

Spatial spectrum estimation for three algorithms. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

Comparisons of the measured and simulated data of phenological stages (day of year) using the different calibration algorithms. by Yonghui Zhang (279832)

Subjects:

List of symbols used in this study. by Yonghui Zhang (279832)

Subjects:

Algorithm and its parameter settings. by Lin Li (28817)

Subjects:

ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

IDRAS algorithm outline. by Ron Teichner (21492434)

Data sources for calibration and evaluation. by Yonghui Zhang (279832)

Subjects:

Filtered Labels after applying the data preparation algorithms. by Tanjim Taharat Aurpa (11250554)

Performance comparison experiments with mainstream object detection algorithms. by Dongshan Jiang (21866339)

A framework for improving localisation prediction algorithms. by Sven B. Gould (12237287)

“…Proteins with non-canonical internal motifs, or those dually targeted need to be taken into account (as they help to better distinguish between pNTS and mNTS features) and validated data could be sorted according to whether it is part of a core- or pan-proteome. …”

Detailed information of the field experiments. by Yonghui Zhang (279832)

Subjects:

The Cultivar-specific parameters to be calibrated in CSPM. by Yonghui Zhang (279832)

Subjects:

Top-rated mode of transport based on the SEU algorithm (SEU scores from 0 to 40). by Johannes Weyer (13392175)