Implementation of AI-Based Image Recognition for Library Book Classification: A Case Study of University of Maiduguri (Maiduguri LGA, Borno State)
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- 1-5 Chapters
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- Table of Content: Available
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- Recommended for :
- NGN 5000
Background of the Study
Library book classification is a time-consuming process that often involves manual cataloging and sorting of books. As libraries grow in size, the task of managing and categorizing books becomes increasingly challenging. AI-based image recognition has the potential to automate this process by accurately identifying and categorizing books based on their covers and other visual features. This study aims to implement an AI-based image recognition system for the classification of library books at the University of Maiduguri, located in Maiduguri LGA, Borno State.
Statement of the Problem
Traditional methods of library book classification at the University of Maiduguri rely on manual cataloging, which is inefficient and prone to errors. The implementation of AI-based image recognition could streamline this process and improve the accuracy and speed of book classification. However, the effectiveness of this technology in the context of Nigerian universities remains underexplored.
Objectives of the Study
1. To implement an AI-based image recognition system for classifying library books at the University of Maiduguri.
2. To evaluate the performance of the image recognition system in accurately classifying books.
3. To assess the impact of AI-based book classification on library efficiency and user satisfaction.
Research Questions
1. How effective is AI-based image recognition in classifying library books at the University of Maiduguri?
2. What impact does the AI-based classification system have on the efficiency of library operations?
3. What challenges are involved in implementing AI-based image recognition for book classification in university libraries?
Research Hypotheses
1. AI-based image recognition will provide more accurate and efficient book classification than traditional manual methods.
2. The implementation of AI for book classification will significantly improve library efficiency and user satisfaction.
3. Challenges in implementing AI-based image recognition will include difficulties in training the model, ensuring system integration, and managing the diversity of book covers.
Significance of the Study
This study will demonstrate the potential of AI-based image recognition in improving the efficiency and accuracy of library book classification. The findings will be valuable to university libraries seeking to modernize their operations and enhance the student experience.
Scope and Limitations of the Study
The study will focus on the implementation of AI-based image recognition for book classification at the University of Maiduguri. Limitations include potential issues with dataset quality, model training, and adapting the system to diverse book cover designs.
Definitions of Terms
• AI-Based Image Recognition: A technology that uses artificial intelligence to analyze and interpret visual data for identifying objects, such as books.
• Library Book Classification: The process of categorizing books into a system for organization and retrieval.
• Automation: The use of technology to perform tasks with minimal human intervention.
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