The history and current situation of computer vision technology at home and abroad

In "Huanzhu Gege", Xiaoyanzi changed a few pictures for Ziwei, and expressed everything she wanted to say to Ziwei. What is this for? Vision.

By understanding the image, you can guess the meaning of the image. Image comprehension is also an aspect of computer vision research. For another example, when a car driver sees a traffic light at an intersection, he will take the corresponding action of stopping at the red light and going at the green light.

It's also visual. By identifying traffic lights, you can make a decision on whether to stop or not. Pattern recognition is also an aspect of computer vision research.

If you can write a piece of software, you can automatically understand what Little Swallow wants to say. Do you think there is a future for this? The Massachusetts Institute of Technology (MIT) recently released a software that can read words and colors.

If you could invent a device that automatically recognizes traffic lights and press on the car, you can help those who suffer from color blindness. Do you think there are any prospects?

Machine vision, currently after 10 years of development, the future development direction is in the **?

If the eye is the window to the mind, then machine vision is the eye of the intelligent world.

Machine vision is an important frontier branch of the artificial intelligence industry, which gives machines the ability to "see" and "perceive" by simulating the human visual system. In the past decade, with the continuous improvement of domestic machine vision technology and products in practice, machine vision has been widely used in intelligent security, automobile manufacturing, electronic consumption and other fields.

In the era of AI-deepened intelligence, cameras, as the perception terminal of machine vision, are becoming more and more intelligent, adapting to complex and changeable environments, seizing fleeting opportunities, and collecting higher-quality data.

Especially in the security industry, in the future, it will be 10 years of machine vision to show the beauty of science and technology, AI technology to remove the false and retain the true, under the tide of new infrastructure, the word intelligence will officially come to the stage. And with the continuous maturity of deep learning and other technologies, the boundaries of the security industry will continue to expand.

Of course, there are opportunities and challenges.

The continuous improvement of various technologies of machine vision requires us to implement the technology more solidly and truly implement it into industrial applications.

In the future, with the blessing of 5G networks, machine vision and artificial intelligence will be deeply integrated, and machine vision will also empower thousands of industries and rapidly promote the in-depth development of various industries.

As an important subfield of artificial intelligence, computer vision has broad prospects and development potential. Here are some of the trends and directions for the future of computer vision:

Technological innovation: With the continuous development and innovation of deep learning, neural networks and other technologies, the performance and capabilities of computer vision will continue to improve, and it is possible to solve more complex vision tasks.

Interdisciplinary integration: Computer vision will have more intersections and integration with other artificial intelligence fields (such as natural language processing, speech recognition, etc.) and other disciplines, providing new ideas and methods for solving complex problems.

Personalization and intelligence: Computer vision systems will be more personalized and intelligent, and can provide customized solutions according to the needs and scenarios of different users.

Real-time and low power consumption: Computer vision technology will make breakthroughs in real-time and low power consumption to meet the needs of mobile devices, Internet of Things, and other applications.

Data security and privacy protection: Computer vision technology needs to process a large number of images and data in the application process, and how to ensure data security and privacy under the premise of practical and efficient vision tasks will become an important issue.

In conclusion, computer vision, as a growing field, has great prospects and potential. With the advancement of technology and the expansion of applications, computer vision will play an increasingly important role in various fields.

My college major was a major that I found after choosing a transfer, which made me suffer for decades, and I would have a lot of consideration if I were to choose a major again. I can think from a variety of perspectives, such as personal interests, future trends, employment opportunities, etc. Most importantly, we need to be mindful of our interests and abilities in order to better grasp opportunities and succeed.

If I had to choose again, I might consider choosing a major related to artificial intelligence and computer vision. Because in the coming years, we can see the importance of these technologies, and that's obvious. The biggest attraction of this field is the integration of monetization and quietness.

I think this kind of profession will lead to higher employment opportunities and higher salaries in the future. In addition, I think that social science majors are also very promising.

In this era, we are facing many social problems, such as climate change, aging population, wealth disparity, and so on. Social science majors can help people better understand and cope with these issues. Another major worth considering is marketing and brand management.

With the rapid development of the Internet and the increasingly fierce competition in the global market, marketing and brand management are becoming more and more important. This major will also have good employment opportunities and development prospects in the future.

Computer vision is a challenging and important research field in both engineering and science. Computer vision is a comprehensive discipline, which has attracted researchers from various disciplines to participate in the study of it. These include computer science and engineering, signal processing, physics, applied mathematics and statistics, neurophysiology and cognitive science, among others.

Vision is an integral part of a wide range of intelligent autonomous systems in applications such as manufacturing, inspection, document analysis, medical diagnostics, and the military. Because of its importance, some advanced countries, such as the United States, have listed the study of computer vision as a major fundamental problem in science and engineering that has a wide impact on the economy and science, the so-called grand challenge. The challenge of computer vision is to develop visual capabilities for computers and robots that are comparable to those of humans.

Machine vision requires image signals, texture and color modeling, geometric processing and reasoning, and object modeling. A capable vision system should have all of these processes tightly integrated. [NEG91] As a discipline, computer vision began in the early 60s, but many important advances in the fundamental research of computer vision were made in the 80s.

Nowadays, computer vision has become a mature discipline that is different from artificial intelligence, image processing, pattern recognition and other related fields. Computer vision is closely related to human vision, and having a correct understanding of human vision will be very beneficial to the study of computer vision. To do this, we'll start with human vision.