Artificial Intelligence

This paper conducts a systematic bibliometric analysis in the Artificial Intelligence (AI) domain to explore privacy protection research as AI technologies integrate and data privacy concerns rise. Understanding evolutionary patterns and current trends in this research is crucial. Leveraging bibliometric techniques, the authors analyze 3,061 papers from the Web of Science (WoS) database, spanning 1994 to 2023.

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This dataset presents a collection of real-world RF signals encompassing three prominent wireless communication technologies: Wi-Fi (IEEE 802.11ax), LTE, and 5G. The data aims to facilitate advanced research in spectrum analysis, interference identification, and wireless communication optimization. The signals were meticulously captured under varying conditions to ensure a broad representation of real-world scenarios, including different modulation schemes, channel conditions, and data rates.

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1176 Views

Our video action dataset is generated using a 3D simulation program developed in Unity. Each data sample consists of a video capturing a human performing various actions. Our initial set of actions comprises a total of 10 different yoga poses: camel, chair, child's pose, lord of the dance, lotus, thunderbolt, triangle, upward dog, warrior II, and warrior III. Within each of these 10 yoga poses, there are four variations, some exhibiting more pronounced differences than others. This results in a total of 40 action types within our dataset.

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Our large scale alpine land cover dataset consists of  229'535 very high-resolution aerial images (50cm) and  digital elevation model (50cm) with land cover annotations  produced by  experts in photo-interpretration . The nine land cover types in our study area include bedrock, bedrock with grass, large blocks, large blocks with grass, scree, scree with grass, water area, forest and glacier. The distribution of pixels among classes presents a typical case of a long-tailed distribution with an imbalance factor, defined as the ratio of the most frequent to the rarest class, close to 1000.

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137 Views

 

Abstract- Cardiovascular diseases (CVDs) remain a sig- nificant global health challenge, emphasizing the critical need for accurate predictive models to address early detec- tion and intervention. This study presents a comprehensive framework for heart disease prediction using advanced ma- chine learning techniques.

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1296 Views

Internet-of-Things (IoT) technology such as Surveillance cameras are becoming a widespread feature of citizens' life. At the same time, the fear of crime in public spaces (e.g., terrorism) is ever-present and increasing but currently only a small number of studies researched automatic recognition of criminal incidents featuring artificial intelligence (AI), e.g., based on deep learning and computer vision. This is due to the fact that little to none real data is available due to legal and privacy regulations. Consequently, it is not possible to train and test deep learning models.

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512 Views

This dataset is associated with TODOS: Thermal sensOr Data-driven Occupancy Estimation System for Smart Buildings. It is a novel system for estimating occupancy in intelligent buildings, TODOS uses a low-cost, low-power thermal sensor array along with a passive infrared sensor. We introduce a novel data processing pipeline that allows us to automatically extract features from the thermal images using an artificial neural network. Through an extensive experimental evaluation, we show that TODOS provides occupancy detection accuracy of 98% to 100% under different scenarios.

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770 Views

Dataset for validation of a new magnetic field-based wearable breathing sensor (MAG), which uses the movement of the chest wall as a surrogate measure of respiratory activity. Based on the principle of variation in magnetic field strength with the distance from the source, this system explores Hall effect sensing, paired with a permanent magnet, embedded in a chest strap.

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408 Views

The daily case data for HFMD (Hand-Foot-and-Mouth Disease) and herpangina were collected from the Children’s Hospital of Chongqing Medical University, a national clinical medical research center of China, spanning from January 1, 2015, to December 31, 2021. This dataset contains the timestamp of each patient's discharge, resulting in a total of 109,096 records for HFMD and 133,869 records for herpangina.

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This dataset, presents the results of motion detection experiments conducted on five distinct datasets sourced from changedetection.net: bungalows, boats, highway, fall and pedestrians. The motion detection process was executed using two distinct algorithms: the original ViBe algorithm proposed by Barnich et al. (G-ViBe) and the CCTV-optimized ViBe algorithm known as α-ViBe.

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153 Views

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