![]() ![]() Additionally, the paper examines the potential benefits and challenges of AI adoption, including the concerns about job displacement and the future of work. The primary focus of the research is on the effects of AI on different job sectors, including healthcare, finance, and transportation. It explores the history of AI and highlights the top AI tools that are being used today. This research paper provides an in-depth analysis of the impact of Artificial Intelligence (AI) on various job sectors. In this article, we will discuss OCR with IBM Watson Natural Language Understanding API, a deep learning-based tool for localizing and detecting the text in documents and images. Getting information from complex structured documents becomes difficult and hence they require some effective methodologies for information extraction. Extracting such data requires some optimised models which can detect and recognize the texts. These documents hold the data mainly in the form of images. OCR (Optical Character Recognition) is part of the data mining process that mainly deals with typed, handwritten, or printed documents. In machine learning, data mining is one of the major sections that cover the extraction of the data from the different platforms. Every image in the world contains any kind of object in it and some of them have characters that can be read by humans easily, programming a machine to read them can be called OCR. By the full form, we can understand it is something that can read content present in the image. OCR is a short form of Optical character recognition or optical character reader. This paper also examines related literature. This paper provides the different uses of text recognition from photographs as well as a discussion of the text recognition module. Many applications depend heavily on text recognition. After that, post processing is carried out to minimise errors. The classification method makes it possible to locate the text in accordance with clearly stated guidelines. The most important data from the image can be extracted using features to help in text recognition. Character separation is aided by the segmentation process. The most important action in the pre-processing step is the conversion of a colour image into a binary image, which separates the text from the backdrop. Pre-processing, segmentation, feature extraction, classification, and post processing are some of the stages in text recognition. This makes it easier to store information and allows for easy retrieval of that information as needed. ![]() The amount of information being stored in digital form instead than on paper has greatly increased in recent years. The method of extracting text from photographs is crucial in the current environment.
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