Computer Science
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A Personalized Mentor Recommendation Letter
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A Complete Research Report
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A Comprehensive Research Experience
[Computer Science]
Document Image Recognition Based on Deep Learning Methods
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Project Introduction
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Formal Research: 1v1 Online Customized Tutoring
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Project Gains: Research Report, Mentor Recommendation Letter
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Research Supplement Package: 48 hours of foundational research courses + 15 hours of academic writing foundational courses
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Involved Fields
This topic involves knowledge related to Computer Vision | Pattern Recognition | Object Detection, suitable for students applying for Computer Vision | Automation | Pattern Recognition | Computer Science and other related majors
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Target Audience
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Students who wish to enhance their knowledge and academic abilities
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Students eager to master cutting-edge research hotspots and methodologies
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Students with intentions to study abroad or pursue further studies in different fields
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Research Frontier
Document image recognition is a classic problem in the field of pattern recognition, playing an important role in its birth and development. Related technologies are widely applied in the recognition and processing systems for documents, checks, mail, receipts, manuscripts, and license plates, bringing numerous conveniences to work in finance, transportation, logistics, education, healthcare, and government affairs, greatly facilitating daily life.
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Research Introduction
This project mainly studies the detection and recognition algorithms for text in document images. In this project, students will learn the basic structure of neural networks to construct a basic recognition network; secondly, by studying classic network structures and the latest papers, they will determine research ideas and plans; finally, based on existing methods, they will attempt to modify hyperparameters or incorporate new structures.
Through this project, students will gain a clear understanding of object detection and recognition networks, master the basic structure and construction methods of neural networks, and enhance their understanding of the deep learning field and research capabilities in text detection and recognition.
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Key Points of the Topic
Research Methods
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1v1 Customized Tutoring Reference Tasks
Mastering Literature Review and Research Methods
· Master methods for reviewing literature and literature-oriented learning;
· Master literature management methods;
· Learn the research hotspots and directions in this field through literature review;
· Master methods for quickly extracting important information from literature.
Task Two
Learning Relevant Basic Knowledge
· Learn the basic knowledge and theories of convolutional neural networks;
· Master the basic knowledge and theories related to visual computing;
· Based on the understanding of existing research content, construct one’s own research ideas.
Task Three
Learning Related Models
· Study network structures such as ResNet;
· Study LSTM-related structures;
· Study CRNN network structures;
· Design research plans, including key research content, model key parameter settings, etc.
Task Four
Conducting Research
· Select appropriate datasets;
· Run trained models to intuitively understand the recognition process;
· Analyze experimental results;
· Modify existing structures;
· Further analyze and compare results.
Task Five
Summary and Recommendations
· Provide a comprehensive review of text recognition methods based on analysis results;
· Comparison of modified methods with other methods;
· Propose suggestions for deficiencies in theoretical analysis and shortcomings in the research process.
Task Six
Project Conclusion
· Write an overall report;
· Prepare a 20-30 minute presentation.
(The above tasks are for reference only; actual tutoring will be based on customized requirements)
More project information
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