Why Visual Data Labeling is Critical to The Success of Computer Vision

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Why it is Important for Computer Vision
Visual Data Labeling
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Computer Vision models are incomplete without
accurate visual data labeling.

• Growing at a CAGR of 7.8, the Computer Vision
  market has been rapidly extending and taking
  businesses by storm.

Source
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Why visual data labeling isimportant for
computer vision

• Streamlined data preprocessing
• Robust datasets
• Precision enhancement
• Easy-to-scale AI ML models
• Continuous improvement

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Streamlined Data Preprocessing

• Accurate tagging / labelling
• Perfect feature extraction
• Accurate data re-scaling

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Robust Dataset

• Noise elimination
• QC-based data
• Quantity data

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Precision Enhancement

• Continuous data feeding
• Perfectly fitted model
• Zero bias

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Easy-to-scale Models

• Voluminous Data Labeling
• Context adjustability
• Execution consistency

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Continuous Improvement

• Constant data addition
• Model retraining
• Statistical refinement

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• Hitech BPO accurately annotated thousands of
  images to be used as training dataset for
  Computer Vision models of a Swiss food waste
  assessment solution provider.

Company

• Swiss food waste assessment company

Business need

• Label thousands of food waste images
• Build a high-accuracy computer vision model

Hitech BPOs visual data labeling solution

• Iterative labeling and segmentation
• Real time visual labeling intelligence

Business impact

• 100 accuracy across categories
• Seamless computer vision modeling efficiency

Click here to read the full case study
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Build scalable computer vision models using
Hitech BPOs high-grade visual data labeling.
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