Structure of the Kuhn-Munkres Algorithm. by Qingnan Ji (22662198)

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

The actual training effect of four algorithms on original photo data (All images are original images taken by the author). by Xiaojun Wang (50332)

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The run time for each algorithm in seconds. by Edward Antonian (21453161)

“…The goal of this paper is to examine several extensions to KGR/GPoG, with the aim of generalising them a wider variety of data scenarios. The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. …”

Statistical test results for multimodal matching accuracy (based on 5-fold cross-validation, n = 5). by Qingnan Ji (22662198)

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The process of matching borrowing and lending banks using the alliance-first matching algorithm. by Ziwen Jiang (1341279)

Preliminary matching algorithm for RANSAC features. by Zhuoheng Xiang (20485194)

Solving process of gradient-based search. by Tarun Khajuria (12117309)

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Algorithm process. by Wei Cui (92129)

The method for determining the chemical constituents of unknown materials in the algorithm. by Dong Hyeok Choi (12562048)

Table 1_An approach for teleseismic location by automatically matching depth phase.xlsx by Jianlong Yuan (460571)

“…<p>To deal with the low efficiency problem of accurate teleseismic hypocenter location, this paper proposes a fully automatic approach by integrating the advantages of Seismic-Scanning based on Navigated Automatic Phase-picking, which can automatically detect and locate seismic events from continuous waveforms, and the Depth-Scanning Algorithm, which can determine the precise focal depth of local and regional earthquakes by matching depth phases. …”

The Search process of the genetic algorithm. by Wenguang Li (6528113)

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The construction process of the FCM clustering algorithm. by Xini Fang (20861990)

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Research process. by Yongjian Zhang (3986126)

“…Using braking deceleration and time to collision, we identified near-crash events and classified them into high, medium, and low severity levels using the DBSCAN clustering algorithm. These near-crash events were then matched to the corresponding road section, assigning different weights based on their severity levels to evaluate the risk level of each segment. …”

Unique phenotypes which were not matched by either algorithm. by Mohammad A. Al-Mamun (6086642)

Zaremba et al. Supplemental Figure S1. Matching of the groups based on height, using two sequential nearest neighbor-matching algorithms. by Solomiia Zaremba (19540666)

Processed results from ECG data with the P-T algorithm. by Daehyun Kwon (11985629)

Calculation algorithm implementing the proposed model. by Landry Djopkop Kouanang (17131748)

Calculation algorithm implementing the proposed model. by Landry Djopkop Kouanang (17131748)

Data (3). by Qingnan Ji (22662198)

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