a. How various statistical models account for modulation classification performance across the entire dataset. by Chris Scholes (3309477)

SSI of the filtering results for the complete image of each algorithm. by Haiyan Zhang (176919)

Subjects:

Augmentation levels with back-translation. by Rodrigo Gutiérrez Benítez (19746443)

mAP results of five algorithms. by Jirong Zeng (20308604)

Subjects:

BER at different SNR levels. by Hui Zhao (7395)

Spatial distribution level results. by Xiaojie Feng (6873953)

Subjects: “…hierarchical clustering algorithm…”

Performance across difficulty levels. by Tarun Khajuria (12117309)

Subjects:

Automatic lithology recognition algorithm while drilling. by Wei Jiang (14986)

Subjects: “…automatic identification algorithm…”

A schematic diagram of the settlement spatial distribution model based on factor analysis integrated with the hierarchical clustering algorithm. by Xiaojie Feng (6873953)

Subjects: “…hierarchical clustering algorithm…”

Nonlinear Granger causality test for Volatility of Bitcoin based on the Parkinson volatility estimator and Bitcoin-based energy consumption. by Georgia Zournatzidou (22453552)

Best-performing BirdNET parameter settings resulting in the highest F1 scores within each temporal aggregation level, based on 1,944 model configurations compared to expert identif... by Andrew J. Fairbairn (22231970)

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

Levels of interest of participants in the predefined topics addressed in the survey. by Diana Ramírez-Cifuentes (20700054)

Feature selection results from the Boruta algorithm. by Junying Wei (1710550)

Subjects:

Summary of major algorithms used for signal detection. by Feilong Tan (14886395)

Clinic structures based on administrative data with clinic-level identifiers (right side) and the comparable network-identified practice based on shared clients (left side). by Megan Kurz (17746658)

Subjects:

The flowchart of Algorithm 2. by Jing Xu (15337)

“…To solve this optimization model, a multi-level optimization algorithm is designed. Based on the sampling averaging approximation method, demand scenarios and passenger no-show scenarios are generated and the optimization problem is decomposed, including the joint optimization of overbooking and seat allocation under a single demand scenario, and the ticket adjustment under other demand scenarios. …”

Nonlinear Granger causality test for Volatility of Bitcoin based on the Garman-Klass volatility estimator and Bitcoin-based energy consumption. by Georgia Zournatzidou (22453552)

Nonlinear Granger causality test for Volatility of Bitcoin based on the Rogers-Satchell volatility estimator and Bitcoin-based energy consumption. by Georgia Zournatzidou (22453552)

Signals detection at the SOC level. by Yongfei Yu (3083934)