Computer Vision, a field of artificial intelligence, enables computers to mimic the way humans see, analyze, and understand the visual world. Through deep learning models and neural networks, computers can break down visual data, draw accurate predictions, and identify the subject matter of images and videos.
While human vision has had the advantage of time – we’ve been interpreting visuals long before computers were even invented – computer vision is taking precision to the next level. Models trained on specific tasks can deliver results more accurately and consistently than the human eye, and this has huge industry applications.
According to IBM, “Because a system trained to inspect products or watch a production asset can analyze thousands of products or processes a minute, noticing imperceptible defects or issues, it can quickly surpass human capabilities.” For more on how this works, consider Fei Fei Li’s explanation of how a computer is taught to read pictures in a TedTalk.
Leaders in medicine, logistics, finance, and more are picking up on the potential of computer vision. No one is turning down the promise of huge increases in accuracy and speed, but many still question if it’ll actually work within their organizations.
How are real businesses operationalizing computer vision today? Let’s take a look at four examples:
1. Fatigue Detection
To improve truck driver safety, logistics and transportation companies are leveraging computer vision to detect fatigue and distracted driving. Smart cameras installed on truck dashboards can monitor facial expressions, body posture and automatically trigger alerts to reduce accidents on the road.
2. Alzheimer’s Early Detection
Another great perk of advancing technology is that we can now leverage computer vision for Alzheimer’s progression stage detection based on Clock Drawing Test (CDT) images of patients. Computer vision can detect changes over time that the human eye may not perceive. Early detection could give the individuals better chance at fighting the disease, and medical professionals more time to treat it as well as reduce the dependency on geriatric psychiatrists for early-stage tests.
3. Satellite Image Processing
The need for ESG actions grows with the rapid progression of climate change. Many industries, governments, environmental professionals are moving fast to meet the needs and accurately using modern technology to help the environment may help accelerate these goals. We can use computer vision for the quantization and monitoring of ESG parameters like air pollution, water quality, waste management, natural resource management, compliance, more.
4. Product Recognition for Retail
Augmented with computer vision, smart scales and POS machines can gather customer analytics, reduce dependency on staff knowledge, reduce user-driven errors, and lower employee training costs. Intel partnered with Evalueserve to leverage IoT in grocery stores. Advanced computer vision and AI technologies were embedded in smart scales and POS devices to make them detect and weigh fresh produce within 0.1 seconds. This eliminated the need to punch in SKUs manually while collecting data to improve the in-store experience.
This computer vision-enabled technology made an enormous impact on the market in China where it was tested. The Chinese manufacturer released its first set of AI-powered scales and received over 150 offers within three hours. Now, the CEO said the company is forecasting over 30,000 orders in the first three months.
The above four examples are just a few among many of the ways we can leverage computer vision to drive change, better analyze markets, detect issues, and more.
Speak to our experts today to learn how you can incorporate AI and computer vision to improve decision-making in real-time. Speak to an expert today, visit https://www.evalueserve.com/speak-to-expert/