Papers with Code 아카이브
Document Image Classification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 8
- 보존된 평가 기록
- 49
Document image classification is the task of classifying documents based on images of their contents.
<span style="color:grey; opacity: 0.6">( Image credit: Real-Time Document Image Classification using Deep CNN and Extreme Learning Machines )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/salesforce/codet5
https://github.com/sdadas/polish-roberta
https://github.com/shabie/docformer
DocFormer: End-to-End Transformer for Document Understanding
https://github.com/simon-benigeri/narrative-generation
https://github.com/skchen1993/TrangFG
Training data-efficient image transformers & distillation through attention
https://github.com/smu-ivpl/DeepfakeDetection
Training data-efficient image transformers & distillation through attention
https://github.com/sunsmarterjie/itpn
https://github.com/thibaultdouzon/long-range-document-transformer
LayoutLM: Pre-training of Text and Layout for Document Image Understanding
https://github.com/thibaultvt/Diard
DiT: Self-supervised Pre-training for Document Image Transformer
https://github.com/tianhai123/vit-pytorch
Training data-efficient image transformers & distillation through attention
https://github.com/tighu20/Kaggle-Tweet-Sentiment-Extraction
https://github.com/traviscoan/cards
https://github.com/ttt496/vit-pytorch
Training data-efficient image transformers & distillation through attention
https://github.com/tuannamnguyen93/DFKI_test_PhD
https://github.com/tuannamnguyen93/test_PhD
https://github.com/uakarsh/TiLT-Implementation
Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformer
https://github.com/utterworks/fast-bert
https://github.com/viethoang1512/kpa
https://github.com/wangyz1608/knowledge-distillation-via-nd
Training data-efficient image transformers & distillation through attention
https://github.com/woctezuma/steam-BEiT
https://github.com/wzzzd/LM_NER
https://github.com/xiaoqian19940510/text-classification-
https://github.com/xiaoqian19940510/text-classification-surveys
https://github.com/yangyucheng000/University/tree/main/model-2/beit
https://github.com/yangyucheng000/University/tree/main/model-3/roberta
https://github.com/yangyucheng000/papercode-2/tree/main/layout-diffusion-mindspore
LayoutLM: Pre-training of Text and Layout for Document Image Understanding
https://github.com/yyk-wew/semanticmim
https://github.com/zaradana/Fast_BERT
https://github.com/zfj1998/CodeBert-Code2Text
https://github.com/zhuhanqing/lightening-transformer
Training data-efficient image transformers & distillation through attention
https://github.com/znhy1024/protoco
https://gitlab.com/birder/birder
Training data-efficient image transformers & distillation through attention
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.