The Vehicle Damage Detection & Recognition system is a high-accuracy process where a set of Machine Learning Algorithms with an API utilizes computer vision. Based on Artificial Intelligence deep learning, the algorithms automatically detect a vehicle's body and analyze the extent of the damage. Image-based convolutional neural networks can accurately recognize car damage through photos and videos.
AI damage inspections can recognize and analyze multiple types of damage in seconds. This way, users can make more informed decisions regarding the condition of their vehicles.
Recognize a Vehicle
Identify Vehicle Elements
Estimate primary damage of vehicle elements and costs
Types of Damages
Vehicle damages can be classified into three primary categories, based on which component they impact. These categories are metal damage, glass damage, and miscellaneous damage.
Metal Damage includes:
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Dent
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Scratch
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Tear
Glass Damage includes:
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Crack
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Chip
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Spider Crack
Miscellaneous Damage includes:
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Dislocation of parts
Why Vehicle Damage Recognition
The solution speeds up data processing, saving the company’s spending on human resources and boosting the process of image data analysis in times. Machine learning algorithms and analytical systems can replace a human-operated time-consuming process of claims proceedings and approvals.
Traditional Process Vs Vehicle Damage Detection & Recognition
