Overview:
In this age of digital transformation, there is a data type that has received minimal focus yet can have significant impacts on a company’s success — visual data.
Computer Vision with artificial intelligence (AI) is capturing the abundant visual data and making sense of it for design engineers, quality teams, production teams, and more.
By employing algorithms and techniques inspired by human vision, computer vision systems can extract meaningful insights from visual data. This technology has widespread applications, including object recognition, image classification, face detection, autonomous vehicles, medical imaging, surveillance, and augmented reality.
Unleashing the power of machines to see and understand the visual world:
Computer vision is an interdisciplinary field that focuses on enabling machines to perceive, interpret, and understand visual information from images or videos. It involves the development and application of algorithms, techniques, and models to extract meaningful insights from visual data.
Computer vision AI is camera agnostic, meaning it can be used with any type of imaging technology. It also leverages the latest in deep-learning technology, which is based on artificial neural networks such as convolutional neural networks (CNN) and recurrent neural networks (RNN).
Design engineers of advanced machines and systems such as robotics, drones, inspections systems, manufacturing lines, and brand-new factories are embedding various types of 2D and 3D imaging technologies along with computer vision.
Engineers rely on computer vision for the development of perception systems in autonomous vehicles. Computer vision algorithms process visual data from cameras, LiDAR, or radar sensors, enabling vehicles to detect objects, navigate, and make decisions in real-time.
By leveraging visual information, engineers can develop advanced systems and technologies that transform industries and solve complex challenges.
Current market landscape:
Computer vision technology is being adopted across various industries. It finds applications in automotive, healthcare, retail, agriculture, manufacturing, security and surveillance, gaming, and augmented reality, among others. Industries are leveraging computer vision for automation, quality control, object detection, predictive maintenance, and immersive experiences.
Retail industry giants are leveraging computer vision and AI to redefine the shopping experience. Hindustan Unilever (HUL) is customizing the assortment of products available at millions of stores based on the customers in the vicinity, their living standards, the product categories they have adopted and more.
Retailers are increasingly deploying smart shelf technology as part of their efforts to digitize their stores, especially in categories like grocery, general merchandise, convenience, consumer electronics and home improvement.
Google has been a leader in computer vision, leveraging its expertise in machine learning and artificial intelligence. Its computer vision projects include Google Photos, Google Lens, and TensorFlow, an open-source deep learning framework widely used for computer vision applications.
The current market landscape for computer vision is dynamic and promising, with increasing adoption across industries and advancements in technology driving its growth.
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