Container OCR
Streamline container movement, reduce idle times and boost security.
Streamline container movement, reduce idle times and boost security.
Container OCR simplifies, expedites and automates container tracking and management, thus making it error-free. It accurately captures and registers container codes along with the time and data. Not only does it help managing the stacked containers, but it also makes the entry/exist faster and contributes to the safety of the depot by denying entry to any unauthorized vehicle.
Manual processes often result in missed or incorrect container codes. It leads to shipment delays and errors.
Standard systems struggle to handle varied container sizes and orientations. It requires manual adjustments.
Slow identification and registration processes create bottlenecks in cargo movement and tracking.
Poor lighting, damaged surfaces or movement reduce the success rate of barcode scanning.
AI Container OCR ensures precise ISO code recognition by reducing human error and increasing reliability.
Effortlessly reads both horizontal and vertical text by allowing seamless operation across container types.
High-speed image and video analysis enables rapid scanning. Even for moving containers by improving efficiency.
Accurately reads barcodes in low light, on damaged surfaces and in motion. It ensures dependable tracking.
Container OCR is beneficial for a wide range of stakeholders within the global supply chain as it transforms how goods are handled by them.
High-resolution cameras are strategically placed to capture images of container codes across various scenarios.
Diverse dataset of container images is gathered, annotated and augmented to train a robust model.
A deep learning model like CNN is trained on the prepared dataset. The hyperparameters are optimized for optimal performance.
The trained model is integrated in existing systems and deployed for real-time processing, with speed and efficiency.
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CEO & Co-founder