Abstract: This study compares the performance of Tesseract, Easy-OCR, and Transformer OCR in recognizing crossed-out text in the Indonesian and English languages. The focus on crossed-out text aims to ...
0.70.x - 0.74.x 1.0.x Old Architecture Fully Supported 0.75.x - 0.78.x 1.0.x Old & New Architecture Fully Supported Note: This library requires prebuild because it uses native iOS Vision Framework and ...
This project supports all types of 2D medical X-ray images, including chest, dental, and others. It performs super-resolution and denoising using a RealESRGAN-based model. The application supports ...
Abstract: Text detection and recognition in natural scene imagery pose formidable challenges due to variations in orientation, distortions, intricate backgrounds, and inconsistent illumination.
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