Why Visual Data Labeling is Important for The Computer Vision to Succeed

Visual Data Labeling Why it is Important for Computer Vision

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.

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Why visual data labeling is important for computer vision  Streamlined data preprocessing  Robust datasets  Precision enhancement  Easy-to-scale AI & ML models  Continuous improvement

Streamlined Data Preprocessing

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

Robust Dataset

 Noise elimination  QC-based data  Quantity data

Precision Enhancement

 Continuous data feeding  Perfectly fitted model  Zero bias

Easy-to-scale Models

 Voluminous Data Labeling  Context adjustability  Execution consistency

Continuous Improvement

 Constant data addition  Model retraining  Statistical refinement

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 BPO’s 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

Build scalable computer vision models using Hitech BPO’s high-grade visual data labeling.

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