Artificial Intelligence
This dataset contains raw FMCW radar signals collected for human localization and activity monitoring in indoor environments. The data was recorded using mmWave radar sensors across two different laboratory settings, designed to simulate real-life scenarios for human detection and localization tasks.
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110 Views
The spectrum of the Laplace-Beltrami (LB) operator is central in geometric deep learning tasks, capturing intrinsic properties of the shape of the object under consideration. The best established method for its estimation, from a triangulated mesh of the object, is based on the Finite Element Method (FEM), and computes the top k LB eigenvalues with a complexity of O(Nk), where N is the number of points.
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128 Views
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15 Views
https://github.com/GraphDetec/MGTAB
MGTAB is the first standardized graph-based benchmark for stance and bot detection. MGTAB contains 10,199 expert-annotated users and 7 types of relationships, ensuring high-quality annotation and diversified relations.
The components in the datasets:
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3 Views
https://github.com/GraphDetec/MGTAB
MGTAB is the first standardized graph-based benchmark for stance and bot detection. MGTAB contains 10,199 expert-annotated users and 7 types of relationships, ensuring high-quality annotation and diversified relations.
The components in the datasets:
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1 Views
https://github.com/PatriciaXiao/TIMME/tree/master/data/P_all
The components in the datasets:
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12 Views
The CyberAlert-25 Dataset is a comprehensive collection of curated cyber threat data, developed to support advanced research in vulnerability detection, classification, and threat intelligence. Aggregated from authoritative sources such as the National Critical Information Infrastructure Protection Center (NCIIPC) and the MITRE Corporation, the dataset focuses on Common Vulnerabilities and Exposures (CVEs), encompassing a total of 29,650 entries.
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141 Views
This dataset is the supporting simulated data for the paper titled "Hidden Border Tunnels: Research on Excavation Monitoring and Excavation Path Prediction." These data are generated through physical simulations and are used to validate the effectiveness of the algorithms proposed in the paper. The dataset includes the coordinates of simulated vibration events, as well as the prediction results of excavation events by various machine learning models, such as RNN, LSTM, GRU, Transformer, CNN_Transformer, and LSTMTransformer.
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51 ViewsThis dataset is the supporting simulated data for the paper titled "Hidden Border Tunnels: Research on Excavation Monitoring and Excavation Path Prediction." These data are generated through physical simulations and are used to validate the effectiveness of the algorithms proposed in the paper. The dataset includes the coordinates of simulated vibration events, as well as the prediction results of excavation events by various machine learning models, such as RNN, LSTM, GRU, Transformer, CNN_Transformer, and LSTMTransformer.
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7 Views
NICU-Care is a high-quality video dataset designed to support visual recognition tasks in Neonatal Intensive Care Unit (NICU) scenarios, including nursing action recognition, object detection, and semantic segmentation. It was constructed in a standardized simulated NICU environment, capturing multi-view RGB videos of professional nurses performing six types of routine caregiving procedures on simulated infants. The dataset provides fine-grained temporal annotations and pixel-level segmentation masks for key objects like nurse hands, medical tools, and infant body parts.
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114 Views