GuanRunwei/FindVehicle
FindVehicle: A NER dataset in transportation to extract keywords describing vehicles on the road
This dataset provides structured information for identifying vehicles from text descriptions, extracting details like color, brand, model, and location. It helps build systems that can understand natural language queries (e.g., "find a white Audi Q7 in the bottom left") and translate them into specific vehicle features. Law enforcement, traffic management, and smart city developers can use this to enhance vehicle identification and retrieval systems.
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Use this if you need to train a system to accurately extract vehicle attributes (color, type, brand, model, location, orientation) from written or spoken requests in a traffic or surveillance context.
Not ideal if your primary goal is image-based vehicle identification without any natural language input, or if you are looking for a pre-built, ready-to-deploy vehicle retrieval system rather than training data.
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Jul 29, 2024
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