Machine Learning

The dataset exemplifies land vehicle targets, tanks, and comprises 1000 time-frequency representation (TFR) images in jpg format with a resolution of 875x656 pixels. Each image is accompanied by labels containing 14 parameters for geometric parameter prediction.

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17 Views

The advancement of machine and deep learning methods in traffic sign detection is critical for improving road safety and developing intelligent transportation systems. However, the scarcity of a comprehensive and publicly available dataset on Indian traffic has been a significant challenge for researchers in this field. To reduce this gap, we introduced the Indian Road Traffic Sign Detection dataset (IRTSD-Datasetv1), which captures real-world images across diverse conditions.

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328 Views

The dataset is built upon a multi-layer multi-domain (MLMD) network topology of a real testbed.

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237 Views

This dataset contains the measurement in an ultrawide band (UWB) system in the 6.5 GHz band, considering the presence of the human body as the only obstacle. There are measurements in line-of-sight condition to compare the results of the analysis performed. The measurements are part of our research on the adverse effects of the body shadowing in pedestrian localization systems. The measurements were obtained in three distinct scenarios.

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719 Views

The dataset created focuses on the Pakistan Military by collecting five types of entities from Wikipedia: weapons, ranks, dates, operations, and locations. An open-source NER annotator was utilized for annotation, ensuring accurate labeling of data. Post-annotation, the data underwent cleaning and balancing processes. The final dataset comprises 660 neutral and 660 anti-military sentiment samples, totaling 1320 samples. This balanced dataset serves as a valuable resource for sentiment analysis, providing insights into public sentiment regarding military-related topics.

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375 Views

The dataset includes Pakistan most popular YouTube videos for each category from year 2021- 2023. There are two kinds of data files, one includes video statistics and other one related to comments on those videos. They are linked by the unique video_id field. Both datasets are merged in final videos file which contains all videos statistics and sentiment extracted from comments. Here’s a breakdown of each column:

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216 Views

The detection of anomalous structures in natural image data is of utmost importance for numerous tasks in the field of computer vision. The development of methods for unsupervised anomaly detection requires data on which to train and evaluate new approaches and ideas. We introduce the MVTec Anomaly Detection (MVTec AD) dataset containing 5354 high-resolution color images of different object and texture categories. It contains normal, i.e., defect-free, images intended for training and images with anomalies intended for testing.

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119 Views

According to US NOAA, unexploded ordnances (UXO) are ”explosive weapons such as bombs, bullets, shells, grenades, mines, etc. that did not explode when they were employed and still pose a risk of detonation”. UXOs are among the most dangerous, threats to human life, environment and wildlife protection as well as economic development. The risks associated with UXOs do not discriminate based on age, gender, or occupation, posing a danger to anyone unfortunate enough to encounter them.

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809 Views

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: 
Wed, 07/03/2024 - 02:30

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