The old newspaper project
In this project, we will create a newspaper image recognition app based on AI which uses Computer Vision, Optical Character Recognition (OCR) technology and Natural Language Processing (NLP) models to recognize, classify and extract information from images of newspapers. The project follows an itera...
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Nanyang Technological University
2024
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sg-ntu-dr.10356-1816812024-12-13T15:45:41Z The old newspaper project Li, JiaGeng Ling Keck Voon School of Electrical and Electronic Engineering EKVLING@ntu.edu.sg Computer and Information Science In this project, we will create a newspaper image recognition app based on AI which uses Computer Vision, Optical Character Recognition (OCR) technology and Natural Language Processing (NLP) models to recognize, classify and extract information from images of newspapers. The project follows an iterative process; it begins with the investigation of Tesseract OCR and Yolov8 in a pre-alpha version to extract text and analyze layout. Having faced limitations we shifted to advanced implementations such as PaddleOCR along with LayoutParser for styling newspaper layouts and document parsing and using GPT-3 models for detailed outline writing of the extracted content., In this report, we describe the project context, technology choices, how we collected data is followed by some challenges we faced while building the application and how we solved those issues to improve the application's functionality. Bachelor's degree 2024-12-13T11:59:04Z 2024-12-13T11:59:04Z 2024 Final Year Project (FYP) Li, J. (2024). The old newspaper project. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/181681 https://hdl.handle.net/10356/181681 en application/pdf Nanyang Technological University |
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Computer and Information Science Li, JiaGeng The old newspaper project |
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In this project, we will create a newspaper image recognition app based on AI which uses Computer Vision, Optical Character Recognition (OCR) technology and Natural Language Processing (NLP) models to recognize, classify and extract information from images of newspapers. The project follows an iterative process; it begins with the investigation of Tesseract OCR and Yolov8 in a pre-alpha version to extract text and analyze layout. Having faced limitations we shifted to advanced implementations such as PaddleOCR along with LayoutParser for styling newspaper layouts and document parsing and using GPT-3 models for detailed outline writing of the extracted content., In this report, we describe the project context, technology choices, how we collected data is followed by some challenges we faced while building the application and how we solved those issues to improve the application's functionality. |
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Ling Keck Voon |
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Ling Keck Voon Li, JiaGeng |
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Final Year Project |
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Li, JiaGeng |
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Li, JiaGeng |
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The old newspaper project |
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The old newspaper project |
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The old newspaper project |
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The old newspaper project |
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The old newspaper project |
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old newspaper project |
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Nanyang Technological University |
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2024 |
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https://hdl.handle.net/10356/181681 |
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