OCR par deep learning — Lecture haute vitesse en production
Traditional OCR systems break on real production lines. Reflections, curved surfaces, low-contrast printing, and product variation degrade reading accuracy. Deep learning OCR handles all of these conditions by learning character shapes rather than matching pixel templates.
Real-world performance
Speed: 800+ units per minute on aluminium cans, 400+ on curved PET bottles
Accuracy: 99.8%+ on expiration dates and batch codes
Character sets: alphanumeric, special characters, multilingual
Traditional OCR systems break on real production lines. Reflections, curved surfaces, low-contrast printing, and product variation degrade reading accuracy. Deep learning OCR handles all of these conditions by learning character shapes rather than matching pixel templates.
Real-world performance
Speed: 800+ units per minute on aluminium cans, 400+ on curved PET bottles
Accuracy: 99.8%+ on expiration dates and batch codes
Character sets: alphanumeric, special characters, multilingual
Traditional OCR systems break on real production lines. Reflections, curved surfaces, low-contrast printing, and product variation degrade reading accuracy. Deep learning OCR handles all of these conditions by learning character shapes rather than matching pixel templates.
Real-world performance
Speed: 800+ units per minute on aluminium cans, 400+ on curved PET bottles
Accuracy: 99.8%+ on expiration dates and batch codes
Character sets: alphanumeric, special characters, multilingual
