Artificial Intelligence

This dataset contains different intestinal polyp datasets, in which the method of dividing test set and training set is the same as that mentioned in most intestinal polyp segmentation methods, where the training set consists of pictures from Kvasir and CVC-ClinicDB, and pictures from the two datasets are mixed into the same training set. The test set clearly indicates the division of the test set from different data sets in the form of folder names, and all images are unified as 352*352.

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Maternal, sexual and reproductive healthcare (MSRH) are sensitive urgent public health issues that require timely trustworthy authentic medical responses. Unfortunately, curative healthcare systems of Low Middle-Income Countries (LMICs) are insufficiently responsive to such healthcare needs. Such needs vary among social groups often founded on social inequalities like income, gender and education.

Last Updated On: 
Sun, 06/30/2024 - 14:01

In the era of advanced artificial intelligence, the integration of emotional intelligence into AI systems has become crucial for developing Responsible Software Systems that are not only functional but also emotionally perceptive. The Microe dataset, a pioneering compilation focusing on micro-expressions, aims to revolutionize AI systems by enhancing their capability to recognize and interpret subtle emotional cues. This dataset encompasses over eight classes of common emotions, meticulously captured and categorized to aid in the synthesis and recognition of micro-expressions.

Last Updated On: 
Tue, 07/16/2024 - 11:30

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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400 Views

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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179 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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254 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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576 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

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