The project at hand leverages the YOLO (You Only Look Once) model, a sophisticated deep learning algorithm renowned for object detection. YOLO excels in real-time image processing, efficiently detecting and classifying multiple objects concurrently. Its notable speed and accuracy render it particularly suitable for applications such as autonomous vehicles and surveillance systems. The project serves as a demonstrative platform, highlighting the seamless integration of YOLO and its capacity for robust and efficient object detection.
Cheque data extraction is a process that involves capturing and interpreting essential information from a physical or digital cheque. Utilizing advanced optical character recognition (OCR) technology, this method extracts key details such as the payee's name, amount, date, and account information. The extracted data is then digitized and organized for efficient record-keeping, reducing manual data entry errors and streamlining financial transactions. This automated process enhances the accuracy and speed of cheque processing, contributing to more efficient and secure financial operations for businesses and financial institutions.