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 lead to inaccurate or incomplete container code reading, causing delays and delivery errors.
Container OCR achieves ISO code recognition rates exceeding 99%, promising reliable and accurate data capture.
Adapting to different container types, sizes, and orientations (horizontal, vertical) takes additional time
Reads both horizontal and vertical container codes, accommodating diverse scenarios with the same speed and precision.
Delays in identifying and registering codes can slow down operations and create bottlenecks.
Container OCR can process images and videos at speeds, even for moving containers, minimizing delays and maximizing throughput.
Difficult to achieve success rates due to poor barcode quality, low lighting or damaged barcodes.
Container OCR can read barcodes with high success in low lights conditions, during movement or even damaged barcodes.
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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