Autonomous vehicle
This dataset was developed using the MOBATSim simulator in MATLAB 2020b, designed to mimic real-world autonomous vehicle (AV) environments. It focuses on providing high-quality data for research in anomaly detection and cybersecurity, particularly addressing False Data Injection Attacks (FDIA). The dataset includes comprehensive sensor information, such as speed, rotational movements, positional coordinates, and labelled attack data, enabling supervised learning.
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371 Views
The safe implementation and adoption of Autonomous Vehicle (AV) vision models on public roads requires not only an understanding of the natural environment comprising pedestrians and other vehicles but also the ability to reason about edge situations such as unpredictable maneuvers by other drivers, impending accidents, erratic movement of pedestrians, cyclists, and motorcyclists, animal crossings, and cyclists using hand signals.
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92 Views
This dataset is made for traditional, machine learning, and deep neural-network-based virtual sensor development and evaluation.
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71 Views
My dataset
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96 Views
The C3I Thermal Automotive Dataset provides > 35,000 distinct frames along with annotated thermal frames for the development of smart thermal perception system/ object detection system that will enable the automotive industry and researchers to develop safer and more efficient ADAS and self-driving car systems. The overall dataset is acquired, processed, and open-sourced in challenging weather and environmental scenarios. The dataset is recorded from a lost-cost yet effective 640x480 uncooled LWIR thermal camera.
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2975 Views
This dataset comprises sensory data of in and out miniature vehicle (mobile sink) movement in the agriculture fields. The dataset is collected from the miniature vehicle using a 9-axis Inertial Measurement Unit (IMU) sensor (MPU-9250) placed on the top of the vehicle. Though the vehicle is small but designed to handle all the hurdles of the agricultural land, such as rough and muddy surface. This dataset aims to facilitate appropriate path planning in the agricultural field for the automatic cultivation of seeds, manure spread, and nutrients insertion.
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2031 Views
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AR-SA
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365 Views