Data and code resources. حسب Sam Hall-McMaster (10343795)

"…<div><p>Generalization from past experience is an important feature of intelligent systems. …"

Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code حسب Goutami Sooda (20714729)

The genome coding scheme. حسب Wenbing Shi (5806160)

الموضوعات:

Algorithm optimization experiment matrix. حسب Gabriel Galeote-Checa (20613878)

Algorithm comparison experiment on the RSOD dataset. حسب Pingping Yan (462509)

الموضوعات:

Source Code and Dataset حسب Swathi Ganesan (14394924)

Algorithm training accuracy experiments. حسب Yingying Liu (360782)

Pseudo code. حسب Xuwei Liu (6034592)

"…The results showed that the mean squared errors on the training and testing sets were 1.2% and 1.1%, and the average absolute errors were 8.3% and 8.1%, respectively. …"

USDA-ARS Tucson, Arizona 2014-2022 Data Reservoir of Field Experiments with Managed Honey Bee Colonies: Annotated Hive Frame Photos: Dataset I حسب Vladimir Kulyukin (21983990)

"…,</p><p dir="ltr">2020_02_27_RR_Hive_Directions_IMG_2540_VK.PNG</p><p dir="ltr">2020_02_27_RR_Hive_Directions_IMG_2540_VK.xml</p><p dir="ltr">2020_02_27_RR_Hive_Directions_IMG_2540_VK.txt</p><p dir="ltr">Each PNG is annotated for the following categories:</p><p dir="ltr">(1) CappedHoneyCell </p><p dir="ltr">(2) CappedWorkerBroodCell</p><p dir="ltr"> (3) EmptyCombCell</p><p dir="ltr">(4) PollenCell</p><p dir="ltr"> (5) UncappedNectarCell</p><p dir="ltr"> (6) UncappedWorkerLarvaCell</p><p dir="ltr">(7) BeeHiveFrame</p><p dir="ltr">The counts on the number of annotated region of interest (ROI) images are as follows:</p><p dir="ltr">CappedHoneyCell: 19,723</p><p dir="ltr">CappedWorkerBroodCell: 21,456</p><p dir="ltr">EmptyCombCell: 20,655</p><p dir="ltr">PollenCell: 13,406</p><p dir="ltr">UncappedNectarCell: 11,009</p><p dir="ltr">UncappedWorkerLarvaCell: 18,283</p><p dir="ltr">BeeHiveFrame: 1001</p><p dir="ltr">Each such ROI can be extracted into a separate image and used in training machine learning algorithms.…"

Hyperparameters of self-supervised learning algorithms used in Experiments 1–5. حسب Lalit Pandey (13195488)

"…<p>Hyperparameters of self-supervised learning algorithms used in Experiments 1–5.</p>…"

An overview of the organization of the study program. حسب Marialuisa Gandolfi (8639238)

الموضوعات:

Overview of the development of the biomarkers in the motor, exteroceptive, interoceptive, and cerebral domains. حسب Marialuisa Gandolfi (8639238)

الموضوعات:

The schedule of enrolment, interventions, and assessments. حسب Marialuisa Gandolfi (8639238)

الموضوعات:

Algorithm comparison experiment on the NWPU VHR-10 dataset. حسب Pingping Yan (462509)

الموضوعات:

The parameter setting of the evolutionary neural network. حسب Wenbing Shi (5806160)

الموضوعات:

The result of RRT for experiment 1. حسب Naeem Ul Islam (19837966)

الموضوعات:

The result of RRT* for experiment 1. حسب Naeem Ul Islam (19837966)

الموضوعات:

S1 Data - حسب Wenbing Shi (5806160)

الموضوعات:

Comparison results of ablation experiments. حسب Chunhua Yang (346871)

The optimal number of clusters identified using the GMM clustering algorithm. حسب Dinh K. Tang (20469082)