USE CASE
Clothes Images Segmentation
Dividing the image into different regions of clothing can create or improve recommendation systems in e-commerce
E - commerce
The use of machine learning in online commerce
Segmentation
Dividing an image into semantically independent segments to determine object boundaries
Data collection
Gathering data for subsequent annotation
Data Labeling
Highlighting objects in photos to train systems to recognize and interpret them
1
week
10,000
photos
Our Partners
CASE DESCRIPTION
Collection of clothing photos through parsing and crowdsourcing
Сustomizable to specific tasks
Annotation by relevant classification classes
With each class precisely outlined by a polygon of a specific color
APPLICATION AREAS OF THE DATASET
Retail:
Detection and computer vision for automatically identifying clothing of various classes, colors, sizes, and other characteristics
Fashion and Style:
Computer vision and classification for creating style recommendations, combining different clothing items, and assisting with the selection of outfits in appropriate sizes, styles, and colors
Advertising and Marketing:
Classification for creating unique and personalized advertising campaigns based on the analysis of clothing styles, preferences, and demographic data of users
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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
Alexey Antushenya
Operations manager
Sergey Razumny
TeamLead Crowd Solutions
Maria Kuzmina
Project manager