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Detr Resnet50 Finetuned Lstabledetv1s9 Lsdocelementdetv1type3 Session6
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Detr Resnet50 Finetuned Lstabledetv1s9 Lsdocelementdetv1type3 Session6

Developed by nsugianto
Object detection model based on DETR architecture, using ResNet50 as the backbone network, fine-tuned on a specific dataset
Object Detection
Transformers
#Document Element Detection#DETR Fine-tuned Model#Table Structure Recognition
Downloads 28
Release Time : 4/20/2024

Model Overview

This model is an object detection model based on the DETR (Detection Transformer) architecture, using ResNet50 as the backbone network and fine-tuned on a specific dataset. Suitable for computer vision tasks such as document element detection.

Model Features

Transformer-based Detection Architecture
Adopts the DETR architecture, leveraging the advantages of Transformers, avoiding complex anchor box designs and non-maximum suppression steps in traditional object detection methods
ResNet50 Backbone Network
Uses ResNet50 as the feature extractor, providing strong feature extraction capabilities
Domain-specific Fine-tuning
Fine-tuned on specific tasks such as document element detection, potentially offering better performance in this domain

Model Capabilities

Object Detection
Document Element Recognition
Image Analysis

Use Cases

Document Processing
Document Element Detection
Identify and locate various elements in documents, such as text blocks, tables, images, etc.
Computer Vision
General Object Detection
Detect and locate various objects in images
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