Artificial Intelligence

3D Gaussian Splatting performs 3D reconstruction by densifying sparse point clouds into Gaussian ellipsoids of the order of 100,000, and the reconstruction results show excellent visual effects. However, the point cloud data derived from 3D Gaussian Splatting is not fully utilized in the reconstruction process. To this end, this paper proposes to optimize the point cloud data derived from 3D Gaussian Splatting to improve the rendering quality of 3D Gaussian Splatting. First, the sparse point cloud is input into 3D Gaussian Splatting for reconstruction.

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Modern automotive embedded systems include a large number of electronic control units (ECU) responsible for managing sophisticated systems such as engine control, ABS brake systems, traction control, and power steering systems. To ensure the reliability and effectiveness of these functions, it is essential to apply rigorous test approaches and standards. The integration of diagnostic functions in automotive embedded systems demands consistent tests and a detailed analysis of data.

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143 Views

Animal habitat surveys play a critical role in preserving the biodiversity of the land. One of the effective ways to gain insights into animal habitats involves identifying animal footprints, which offers valuable information about species distribution, abundance, and behavior.

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181 Views

Data sources of MKG with structured medical knowledge database and unstructured scientific publications

Source Type

Name

Related researches

Structured medical knowledge database

KEGG

[20]

SIDER

[21]

ICD-10

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149 Views

The dataset aims to compile images of buildings with structural damage for analysis. The images can be classified by the severity of damage to building facades after seismic events using deep learning techniques, particularly pre-trained convolutional neural networks and transfer learning. The analysis can precisely identify structural damage levels, aiding in effective evaluation and response strategies.

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260 Views

The Defect Tracking dataset provides a comprehensive resource for software maintenance and defect prediction research. This dataset, downloaded from the Jira Spring website, includes detailed defect data from a variety of Spring application projects such as Spring Framework, Spring Boot, Spring Security, Spring Data, and others. It encompasses numerous attributes, including issue summaries, types, statuses, priorities, resolution details, and additional relevant information.

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584 Views

This is the MRI scan database used in the research work of classifying Meningioma Tumor in humans by using hybrid Ensemble Deep Learning Network  AlGoRes. It consist of two sets; one for training and another one for testing the Deep Learning Network  AlGoRes.

Training data set consist of 822 imagers with meningioma_tumor and 395 images without tumor.

Testing data set consist of 115 imagers with meningioma_tumor and 104 images without tumor.

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184 Views

This study utilizes the annual loan ledger data obtained from a commercial bank located in Jiangsu Province, China, which is called ChinaZJB. The ChinaZJB dataset consists of 1,329 valid samples of SMEs after merging the non-financial behavioral information and soft information on credit rating with the financial information, loan information, and non-financial basic information found in the annual loan ledger data.

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597 Views

This large dataset includes six small datasets, including two types, one contains the original node relationship information and node feature information, please use it through the common network construction methods; the other is the dataset which has been processed, including the direct edge information and node's association information, which can be used to construct the network directly through the network construction methods.

 

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256 Views

The LuFI-RiverSnap dataset includes close-range river scene images obtained from various devices, such as UAVs, surveillance cameras, smartphones, and handheld cameras, with sizes up to 4624 × 3468 pixels. Several social media images, which are typically volunteered geographic information (VGI), have also been incorporated into the dataset to create more diverse river landscapes from various locations and sources. 

 

Please see the following links: 

 

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