In the modern world driven by competition, winning a competitive edge is crucial for businesses of any size. This can be achieved with the help of various technological advancements, including artificial intelligence (AI), machine learning (ML), blockchain, or computer vision.
For instance, such big companies like Meta or Google are driven by innovation and constantly strive for the implementation of new technology, which makes these organizations some of the most well-known players in the business arena. Innovation is even more crucial when the business operates primarily in the internet realm, such as any e-commerce company.
For more on business and AI, read these AITJ articles: How AI Benefits Small Businesses and Connecting the Business to Data Science with ModelOps.
In this article, we focus on how computer vision helps businesses improve. But first, we need to explain the concept of computer vision to define the benefits this technology might bring to businesses.
What Is Computer Vision
Being one of the most compelling types of AI, computer vision is the field of computer science that tries to replicate the human vision system and enable computers to process the surrounding (like images or videos) as humans do.
Even though this technology has constantly developed, its capacity is still limited and there is room for improvement. However, thanks to the recent advancements in AI, deep learning, and neural networks, the process of detecting and identifying objects has improved in recent years. In some cases, computer vision even surpasses human capabilities in detecting objects.
The exploration of computer vision started in the 1950s, and the technology was generally utilized for distinguishing between handwritten and typed texts 20 years later. Nowadays, computer vision is utilized in such industries as transportation, healthcare, manufacturing, construction, agriculture, retail, and business.
The Development of Computer Vision
At the beginning of computer vision exploration, all steps and operations, such as creating databases, annotating images, entering data points, capturing new images, and more, were completed manually. However, with the development of machine learning and deep learning, a different approach to solving CV problems was suggested.
Deep learning relies on neural networks and, in this way, significantly improves computer vision. For instance, in the case of facial recognition, with the help of training, algorithms can be taught to detect faces without constant human supervision.
For more on neural networks, read these AITJ articles: Gato, GPT-3 and DALL-E: What are Generalist Agents and how close are we to AGI? and CNN, GNN, and GAN: What Are They?
Computer Vision in Various Industries
The most typical uses of computer vision include:
- Object classification, identification, verification, tracking, and counting
- Facial recognition
- Action recognition
- Forecasting behavior,
- Crowd dynamics
- Object character recognition
- Document analysis.
These functions found application in various industries, as mentioned before. So, let’s take a look at how CV can benefit businesses working in these industries.
In terms of manufacturing, computer vision can improve the functioning of assembly lines and reduce numerous product defects. The system can process visual information and predict possible machine downtimes by utilizing this technology. In addition, CV systems can analyze and monitor the production line and inform supervisors in case any defect occurs.
Businesses in the retail industry can also benefit from the implementation of computer vision. These benefits include improved customer demographics, new insights into product visibility and aisle arrangements, eye movement tracking, anti-theft systems, and better product management.
Healthcare is one more industry where computer vision systems may improve various processes. For instance, CV tools can be implemented in autism and dyslexia identification in children. Additionally, computer vision can facilitate and secure indoor navigation for visually impaired people. And imaging tools, in combination with computer vision, can detect tumors, cancers, and other ailments within the body much faster.
In the case of insurance, computer vision tools can help in identifying legal claims and forwarding them to the right person. Additionally, CV systems can significantly improve risk management and send breakdown alerts.
And one of the most popular computer vision applications is in the automotive industry, especially in the development of self-driving cars. CV systems facilitate object recognition and allow self-driving vehicles to operate safer.
Computer vision is one of the top tech trends this year that can facilitate and streamline many processes within businesses. Hence, we can expect that CV will reach significant improvement and penetrate various industries in the near future.
Hanna is a first-year student at the University of Nicolaus Copernicus, Torun. After leaving her previous university in Belarus, she moved to Poland to study Cognitive Science and its application in Marketing. She is deeply interested in modern technologies, specifically AI and Metaverse, and their influence on society.