Who are the leading innovators of AI-assisted OCR in the tech industry?

The technology industry continues to be a hotbed of innovation, driven by technological advances, increased connectivity, the urgency to make companies more efficient and competitive in an ever-changing marketplace, and the growing importance of technologies such as: activities are promoted by Machine learning, deep learning, natural language processing, computer vision. Together, these technologies improve the accuracy, speed, and reliability of optical character recognition (OCR) tasks, allowing you to efficiently and effectively extract text from images and scanned documents. According to GlobalData’s report on ‘Innovation in Artificial Intelligence: AI-Assisted OCR’, over 3.6 million patents have been filed and granted in the tech industry in the last three years alone.

However, not all innovations are the same, nor do they follow a constant upward trend. Instead, their evolution takes the form of an sigmoidal curve that reflects a typical life cycle from early emergence to accelerated introduction and finally to reaching stable maturity.

Identifying specific innovations, especially those in the emerging and accelerating stages, is essential to understanding the current level of adoption and the expected future trajectory and impact.

Over 300 innovations shape the tech industry

GlobalData’s Technology Foresights uses an innovation strength model built on over 2.5 million patents to plot the S-curve of the tech industry, with more than 300 areas of innovation shaping the industry’s future.

Within emerging The innovation stage, finite element simulations, ML-enabled blockchain networks, and generative adversarial networks (GANs) are disruptive technologies that are in the early stages of application and should be followed closely. Demand forecasting applications, intelligent embedded systems, and deep reinforcement learning are some of them. To accelerate An area of innovation where adoption is steadily increasing.in mature Innovative areas are wearable physiological monitors, smart lighting and smart climate control systems, which are now well established in the industry.

Artificial intelligence innovation S-curve in the tech industry

AI-assisted OCR is a key innovation area in artificial intelligence

AI-assisted Optical Character Recognition (OCR) is an advanced technology that harnesses the power of artificial intelligence (AI) and machine learning algorithms to identify and extract text from digital images and scanned documents. This innovative technology quickly converts printed or handwritten documents into machine-readable text, eliminating the need for time-consuming manual data entry. AI-assisted OCR automates the process, greatly streamlining workflows and increasing productivity.

GlobalData’s analysis also reveals the companies at the forefront of each innovation area and assesses the potential scope and impact of patent activity across different applications and geographies. According to GlobalData, there are over 110 companies working to develop and apply AI-assisted OCR, ranging from technology vendors, incumbents and up-and-coming startups.

AI-Assisted OCR Leaders – Disruptive Innovations in the Tech Industry

‘Application Diversity’ measures the number of different applications identified for each relevant patent and broadly divides companies into ‘niche’ or ‘diverse’ innovators.

“Geographic coverage” refers to the number of different countries in which each relevant patent is registered, reflecting the breadth of intended geographic application, ranging from “global” to “local” .

Number of patents related to AI-assisted OCR

Source: GlobalData Patent Analytics

Samsung is one of the leading patent applicants in AI-assisted OCR. The company’s patents cover a client device consisting of a neural network, including a processor, memory, user interface, communication interface, power supply, and input device, the memory containing a trained neural network received from a server. . A system with trained and configured neural networks for client devices. He has also applied for patents related to server systems and neural network training methods.

Other prominent patent applicants in this field include ADOBE and Alphabet.

In terms of geographic reach, PlusAI leads the way, followed by KDDI and Magic Leap. In terms of application diversity, Enlitic takes the top spot, followed by Memjet Technology and Butterfly Network.

The importance of AI-assisted OCR is to streamline operations, improve data accuracy, reduce costs, improve searchability, ensure compliance, enable data analysis, and support multilingual recognition.

To better understand how artificial intelligence is transforming the tech industry, visit GlobalData’s latest Thematic Research Report on Artificial Intelligence (AI) – Thematic Intelligence.