# High-precision recognition

An ultra-lightweight Korean text line recognition model that supports the recognition of Korean and numeric characters, with an average accuracy of 60.21%.

An ultra-lightweight Latin text line recognition model developed by the PaddleOCR team, supporting the recognition of Latin and numeric characters.

An ultra-lightweight Arabic letter recognition model developed by the PaddleOCR team, supporting the recognition of Arabic letters and numeric characters.

YOLOv8 is an efficient object detection model developed by Ultralytics, based on the YOLO (You Only Look Once) architecture, suitable for real-time object detection tasks.

Focus on extracting and converting text information from images into editable text content

Malicious SQL detection model trained on Keras 3.x, capable of identifying various SQL injection attack vectors

YOLOv10 is a real-time end-to-end object detection model with efficient inference speed and high detection accuracy.

YOLOv10 is a real-time end-to-end object detection model with efficient latency-accuracy and size-accuracy trade-offs.

YOLOv10 is an efficient real-time object detection model developed by Tsinghua University's MIG Lab, offering end-to-end detection capabilities.

MAGE is a model designed to detect machine-generated text in open environments, aiming to identify AI-generated text content.

A BERT fine-tuned SMS classification model for distinguishing spam from non-spam messages.

This model is a fine-tuned version of ConvNeXt-Tiny based on the image folder dataset, suitable for image classification tasks.