#5 Create Your Own Invoice Extractor | Deriving Precision & Recall скачать в хорошем качестве

#5 Create Your Own Invoice Extractor | Deriving Precision & Recall

🎯 Create Your Own Invoice Extractor | Deriving Precision & Recall 🚀 Welcome to Part 5 of the Invoice Extraction series! With Vision Language Models (VLM) improving rapidly, this series will guide you step-by-step on how to use these models to extract key information from invoices. In this video, we’ll derive the precision and recall metrics for invoice extraction. 🔥 Series Outline: ✅ Part 1: Introduction -    • #1 Create Your Own Invoice Extractor ...   ✅ Part 2: Exploring the Invoice Dataset -    • #2 Create Your Own Invoice Extractor ...   ✅ Part 3: Creating a Baseline -    • #3 Create Your Own Invoice Extractor ...   ✅ Part 4: Deriving Accuracy Metric -    • #4 Create Your Own Invoice Extractor ...   ✅ Part 5: Deriving Precision and Recall -    • #5 Create Your Own Invoice Extractor ...   ✅ Part 6: Optimizing Inference with VLLM -    • #6 Create Your Own Invoice Extractor ...   ✅ Part 7: Fine-Tuning Vision Language Models -    • #7 Create Your Own Invoice Extractor ...   ✅ Part 8: Creating a Web Interface -    • #8 Create Your Own Invoice Extractor ...   ✅ Part 9: Recap and Conclusions -    • #9 Create Your Own Invoice Extractor ...   📌 Link to the Notebook: https://github.com/srinathmkce/TheAIG... Citation CORD: A Consolidated Receipt Dataset for Post-OCR Parsing ``` @article{park2019cord, title={CORD: A Consolidated Receipt Dataset for Post-OCR Parsing}, author={Park, Seunghyun and Shin, Seung and Lee, Bado and Lee, Junyeop and Surh, Jaeheung and Seo, Minjoon and Lee, Hwalsuk} booktitle={Document Intelligence Workshop at Neural Information Processing Systems} year={2019} } ``` Post-OCR parsing: building simple and robust parser via BIO tagging ``` @article{hwang2019post, title={Post-OCR parsing: building simple and robust parser via BIO tagging}, author={Hwang, Wonseok and Kim, Seonghyeon and Yim, Jinyeong and Seo, Minjoon and Park, Seunghyun and Park, Sungrae and Lee, Junyeop and Lee, Bado and Lee, Hwalsuk} booktitle={Document Intelligence Workshop at Neural Information Processing Systems} year={2019} } ``` OCR-free Document Understanding Transformer 🍩 ``` @article{kim2021donut, title={OCR-free Document Understanding Transformer}, author={Kim, Geewook and Hong, Teakgyu and Yim, Moonbin and Nam, JeongYeon and Park, Jinyoung and Yim, Jinyeong and Hwang, Wonseok and Yun, Sangdoo and Han, Dongyoon and Park, Seunghyun}, journal={arXiv preprint arXiv:2111.15664}, year={2021} } ```