USE CASE
Cars 360 Video Collection
Dataset for training a neural network for classification of damages in 360-degree videos captured around vehicles
Computer Vision
Ability to recognize and analyze images and videos
Classification
Ability to assess and distinguish objects based on predefined criteria
Transportation
Utilization of machine learning in the automotive industry
Data Collection
Gathering relevant data for subsequent labeling
4
weeks
2,000
videos
Our Partners
CASE DESCRIPTION
Collecting video files of 1.5 to 2 minutes duration, shot around cars using smartphone cameras (iOS and Android)
The dataset can be collected with data from countries of interest, under specific lighting conditions, times of day, and seasons
Additional annotation: bounding box, tracking, and segmentation
APPLICATION AREAS OF THE DATASET
Automotive industry:
Computer vision for analyzing and enhancing safety technologies and driver assistance systems. It can aid in the development of autonomous vehicles, traffic management systems, or diagnostics of technical issues
Damage Identification:
Computer vision for detecting the presence and localization of damage on vehicles
Safety:
Computer vision and classification for identifying vehicles involved in accidents through external surveillance cameras
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Why
Training Data
- Quality Assurance:
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Enhanced Data Accuracy
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Consistency in Labels
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Reliable Ground Truth
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Mitigation of Annotation Biases
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Cost and Time Efficiency
- Data Security and Confidentiality:
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GDPR Compliance
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Non-disclosure agreement
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Data Encryption
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Multiple data storage options
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Access Controls and Authentication
- Expert Team:
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6 years in industry
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35 top project managers
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40+ languages
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100+ countries
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250k+ assessors
- Flexible and Scalable Solutions:
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24/7 availability of customer service
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100% post payment
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$550 minimum check
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Variable Workload
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Customized Solutions
Team leads project
Anton Tseluiko
Operations manager
Arthur Kazukevich
Python-developer
Daria Yurkevich
Quality Control Manager