USE CASE
Legs Images Segmentation
A dataset for training a neural network in the tasks of segmenting parts of the legs using original photographs and corresponding masks with segmentation
Computer Vision
The ability to recognize and analyze images and video
Segmentation
Dividing an image into semantically independent segments to determine the boundaries of objects
E - Commerce
Using machine learning in online trading
Data Labeling
Highlighting objects in photos for training the system to recognize and interpret them
5 000
photos
2 weeks
project duration
Our Partners
CASE DESCRIPTION
Collection of foot photographs through crowdsourcing platforms
Segmentation: foot and the rest of the leg
Data were collected on international crowdsourcing platforms and by an internal team of AI trainers. The collection rate is estimated at 25,000 photographs per month
APPLICATION AREAS OF THE DATASET
Medicine:
Computer Vision for analysis and diagnosis of various diseases of the foot and shin, determining wounds, ulcers, pressure sores, and other problems related to the foot
Visualization and Animation:
Segmentation and Keypoint labeling for use in computer graphics and animation to create realistic models of the foot and its movements
Training and Education:
Segmentation for teaching students and medical professionals to analyze and diagnose foot-related problems
E-commerce
Segmentation and computer vision for automatic shoe size determination and selection of suitable products for customers
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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
Wadim Starosotnikow
Senior quality control manager
Arthur Kazukevich
Python-developer
Maria Kuzmina
Project manager