SOTA OCR with Core ML and dots.ocr

Finetuning olmOCR to be a faithful OCR-Engine

Introducing Mistral OCR 3

Supercharge your OCR Pipelines with Open Models

Mistral OCR

Color Independent Word Segmentation From Transcribed Bangla Passages

The paper presents a color‑independent word segmentation method for handwritten Bangla text images. It works on smartphone‑captured images regardless of paper color or ink type, and the custom dataset includes various real‑world challenges such as shadows. The system achieves 90.60 % recall, 91.80 % precision, and 91.20 % F1‑score on 7,374 words.

ClinOCR-Bench: A Comprehensive Clinical Scanned Document Dataset for Optical Character Recognition Model Evaluation

arXiv:2607. 03650v1 Announce Type: cross Abstract: Extracting textual information from scanned medical documents, such as external laboratory reports and manually filled forms, has been a major challenge in modern electronic health records (EHRs).