Artificial Intelligence
The dataset was specifically created to address the need for violence detection in surveillance systems. It consists of self-recorded videos simulating different types of violent activities relevant to college environments. The dataset is organized into four distinct classes:
Slap
Punch
Kick
Group Violence
Others - Over Crowding, Loitering, Assault, Abuse
Each video is labeled according to its corresponding class to facilitate supervised learning for violence detection models.
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To train critique models capable of delivering step-level supervision and constructive feedback for reasoning, we introduce AutoMathCritique—an automated and scalable framework for collecting critique data.
This framework consists of three main stages: flawed reasoning path construction, critique generation, and data filtering. Using AutoMathCritique, we create a dataset containing $76,321$ samples named MathCritique-76k.
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The proper evaluation of food freshness is critical to ensure safety, quality along with customer satisfaction in the food industry. While numerous datasets exists for individual food items,a unified and comprehensive dataset which encompass diversified food categories remained as a significant gap in research. This research presented UC-FCD, a novel dataset designed to address this gap.
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This dataset comprises raw CAN bus messages collected from five different EV car manufacturers. The primary focus of the dataset is on battery-related messages, although it also includes other general car communication messages. These raw CAN bus messages represent the fundamental data exchanged between various components of the electric vehicle, such as the battery management system (BMS), motor controller, and other electronic control units (ECUs).
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The U.S. delay dataset is collected from Kaggle(https://www.kaggle.com/datasets/robikscube/flight-delay-dataset-20182022), covering three years of flight data from January 1, 2017, to December 31, 2019. The dataset originally collected includes data from 360 airports. We remove airports with fewer annual flight numbers and select data from 75 medium and large airports for our experiments.
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The dataset was developed as part of the NANCY project (https://nancy-project.eu/) to support tasks in the computer vision area. It is specifically designed for sign language recognition, focusing on representing joints and finger positions. The dataset comprises images of hands that represent the alphabet in American Sign Language (ASL), with the exception of the letters "J" and "Z," as these involve motion and the dataset is limited to static images.
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FLAME2-DT (Forest Fire Detection Dataset with Dual-modality Labels) is a comprehensive multi-modal dataset specifically designed for UAV-based forest fire detection research. The dataset consists of 1,280 paired RGB-thermal infrared images captured by a Mavic 2 Enterprise Advanced UAV system, with high-resolution (640×512) and precise pixel-level annotations for both fire and smoke regions. This dataset addresses critical challenges in forest fire detection by providing paired multi-modal data that captures the complementary characteristics of visible light and thermal imaging.
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Missing traffic data caused by sensor failures or communication errors significantly hinders the efficiency of downstream tasks in Intelligent Transportation Systems (ITS), such as the critical functions of traffic monitoring and decision-making. Considering the complex distribution of missing data, it is essential to incorporate the missing features to extract dynamic spatial-temporal correlations in traffic processes. Motivated by these concerns, a novel Dynamic Spatial-Temporal Imputation Network with Missing Features (DSTMIN) is proposed to accurately impute traffic data.
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This dataset provides a comprehensive exploration of 1580 distinct Hindi dish categories, offering a cultural and culinary lens into India's rich gastronomic heritage. The classification encapsulates a diverse array of dishes spanning regional, seasonal, and festive cuisines, while highlighting the integral role of ingredients, cooking techniques, and cultural narratives.
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