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Document Image Classification On Tobacco 3482

Metriken

Accuracy

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname
Accuracy
Paper TitleRepository
Multimodal Side-Tuning (ResNet50)90.30Multimodal Side-Tuning for Document Classification-
DocBert [DOCBERT]91.95Efficient Document Image Classification Using Region-Based Graph Neural Network-
Eff-GNN+ Word2Vec [word2vec]73.5Efficient Document Image Classification Using Region-Based Graph Neural Network-
Multimodal Side-Tuning (MobileNetV2)90.50Multimodal Side-Tuning for Document Classification-
DocXClassifier-L95.57DocXClassifier: High Performance Explainable Deep Network for Document Image Classification
VGG-Efficient Document Image Classification Using Region-Based Graph Neural Network-
Eff-GNN + Word2Vec [word2vec]91Efficient Document Image Classification Using Region-Based Graph Neural Network-
Eff-GNN + Word2Vec [word2vec] + Image Embedding77.5Efficient Document Image Classification Using Region-Based Graph Neural Network-
BERT [BERT]79Efficient Document Image Classification Using Region-Based Graph Neural Network-
DocBERT [DOCBERT]82.3Efficient Document Image Classification Using Region-Based Graph Neural Network-
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Document Image Classification On Tobacco 3482 | SOTA | HyperAI