Y

Yolov8s Table Extraction

Developed by keremberke
A table detection model based on YOLOv8 for identifying table regions in images, supporting both bordered and borderless table detection.
Downloads 5,926
Release Time : 1/29/2023

Model Overview

This model is specifically designed for table detection tasks, capable of efficiently and accurately locating table regions in images, suitable for scenarios such as document digitization.

Model Features

High-precision Detection
Achieves 98.376% mAP@0.5 accuracy on the table extraction validation set.
Dual-category Support
Can detect both bordered and borderless table types simultaneously.
Lightweight Architecture
Based on the YOLOv8s small architecture, balancing performance and efficiency.

Model Capabilities

Table Region Detection
Document Image Analysis
Object Detection

Use Cases

Document Digitization
Scanned Document Processing
Automatically extract table regions from scanned PDFs or images.
Improves efficiency in document digitization processing.
Preprocessing for Table Data Extraction
Provides table region localization for OCR systems.
Enhances the accuracy of subsequent table content recognition.
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
© 2025AIbase