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. …”

Comparison of Multiple Runs of Same Algorithm on the Same Dataset (UNSW-NB15). by Muhammad Rehan Naeem (21432852)

Template- and subject-Level QSM and T1w contrasts with regional segmentation overlays. by Fahad Salman (6150395)

Kurtograms of different signals. by Hang Zhao (143592)

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Number of different types of road sections with different risk levels. by Yongjian Zhang (3986126)

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<i>RMSE</i> comparison using all investigated methods in Table 1: RTC-F solar cell. by Ziad M. Ali (12516532)

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<i>RMSE</i> comparison using all investigated methods in Table 2: PWP201 solar module. by Ziad M. Ali (12516532)

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Spatial clusters of pyrogeographic areas within the La Sepultura Biosphere Reserve based on environmental, social, and fire-related attributes, using a Ward-like clustering algorit... by Christoph Neger (21982924)

Provides a high level view of multi-stage gaze-controlled virtual keyboard using eye tracking produced by the authors. by Verdzekov Emile Tatinyuy (19959261)

Model classification evaluation indicators under various machine algorithms. by Jinlin Teng (17972595)

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Comparing true-predicted values of the top 2–3 categories in different-level attractions in the two provinces. by Lu Xiao (314030)

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The average risk recognition result using different optimisation methods. by Jiaqing Huang (5018492)

Operational mechanism diagram of deep reinforcement learning retrieval optimization module, based on the user interaction retrieval strategy optimization process, encodes the user query vector, historical interaction record and knowledge graph subgraph representation into state space, designs reward function, and trains the policy network through the proximal policy optimization algorithm (PPO) to optimize the retrieval strategy. by Yali Chen (24494)

“…<p>Operational mechanism diagram of deep reinforcement learning retrieval optimization module, based on the user interaction retrieval strategy optimization process, encodes the user query vector, historical interaction record and knowledge graph subgraph representation into state space, designs reward function, and trains the policy network through the proximal policy optimization algorithm (PPO) to optimize the retrieval strategy.…”

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

“…In the software layer of the object detection system, an algorithm that combines YOLOv5s and laser detection was used, and an appropriate instance batch normalization network module was introduced in the YOLOv5s algorithm to improve the model’s generalization ability. …”

Diagnostics and Guide on using diagnostics to infer misclassification error. by Gowtham A. Rao (8261928)

F1 scores measuring BirdNET accuracy compared to expert identification when including or not including week of the year, tested across four temporal aggregation levels with various... by Andrew J. Fairbairn (22231970)

Distribution of consumer’s overconfidence level. by Silvia Merdikawati (20298266)

Comparison of model mean accuracy for the effectiveness of the VRA—fluorescence subtraction algorithm over 450 iterations. by Tri Ngo Quang (20390189)

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

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Number of identified metabolites for each dataset, considering the algorithm, incubation conditions, and acquisition mode (in case of dataset-3). by Paula Cifuentes (22050278)

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