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Fine-tuning YOLOv11 to detect stamps and signatures on banking documents - a practical walkthrough

DEV Community·Muhammad umair akram·about 1 month ago
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Every day, banking ops teams manually review thousands of documents -  loan applications, KYC forms, contracts - looking for the right stamps,  the right signatures, in the right places. It's slow, expensive, and  exactly the kind of work computer vision was made to automate. The catch is that most YOLO tutorials online teach you to detect cars,  dogs, or people in natural photos. None of that translates cleanly to  documents. Documents are structured, scanned at varying quality, often  photographed on phones at angles, sometimes faxed, frequently watermarked, and almost never lit consistently. The model that detects stamps on a  clean PDF will collapse on a phone-shot photo of the same form. "Over the past few weeks I've been deep in shipping a YOLOv11-based  detector for stamps and signatures on documents in a regulated banking  environment." The work taught me where the off-the-shelf tutorials end and where the  real engineering begins.…

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