Libraries at University of Nebraska-Lincoln
Date of this Version
4-15-2024
Document Type
Article
Abstract
This study explores the latest advancements in efficient text and image recognition methods, highlighting their significance and potential applications in libraries and information centers. This study delve into cutting-edge technologies, such as deep learning and computer vision, which have revolutionized how text and images are recognized and interpreted. In the ever-evolving digital landscape, the need for efficient methods for text and image recognition has become paramount. With the proliferation of digital content across various platforms and the exponential growth of data, the ability to accurately and rapidly identify, process, and understand text and images has significant implications for numerous fields, including information retrieval, content analysis, and artificial intelligence. Furthermore, the study explores efficient recognition methods' impact in practical applications, including text-to-speech conversion, image-based search engines, and automated content moderation. The study emphasises these methods' potential benefits in enhancing user experiences, improving content accessibility, and streamlining content analysis. The paper also addresses the challenges faced in recognising texts and images, such as funding, epileptic power supply, and infrastructure. Solutions to these challenges, such as providing digitalization equipment, alternative power supply, and training on digitization skills, are discussed in detail.