What are the application scenarios for machine learning?

There are two most typical types of problems in machine learning: clustering and classification. The former divides a group of people into three groups based on their height; The latter is to tell you the height of some people and their nationality, and then give you the height of some people so that you can judge their nationality.

The core idea is to make the seemingly omnipotent program achieve a breakthrough in mechanical technology and the use of a large area of lower cost, as if domestic and foreign are on the same starting line. I think the domestic environment is better, but the team ability is not strong, and the relevant technology is not mature, but it is not excluded that the emergence of new technologies to break the monopoly of the machinery manufacturing industry, the starting point is the same, it depends on the team ability and learning direction. Of course, there has to be an English god, I don't believe in the existence of genius, because it is the technological achievements of the times that have launched geniuses, and everyone is working hard, but there is only one halo.

Machine learning (ML) is a multi-disciplinary discipline involving probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory and other disciplines. It specializes in how computers simulate or implement human learning behaviors in order to acquire new knowledge or skills, and to reorganize existing knowledge structures to continuously improve their own performance.

It is the core of artificial intelligence, the fundamental way to make computers intelligent, and its applications cover all fields of artificial intelligence, and it mainly uses induction, synthesis rather than deduction.

What is machine vision

In the so-called "vision", the eyes see as "vision", and the signals emitted by the neural activity of the cerebral cortex are "sense". Machine vision refers to the process of using visual sensing equipment (i.e., cameras) to obtain the target image or signal of Younai, transmitting the obtained signal to a special image processing system, and finally obtaining the relevant information of the target. It consists of a hardware facility that displays external information as a digital signal through imaging, and a software that processes and analyzes these signals.

Among them, hardware facilities refer to various camera and photography equipment, light source lighting equipment and image storage equipment; Software is artificial intelligence algorithms, including traditional image processing algorithms, emerging machine deep learning algorithms, etc.

The workflow of machine vision is similar to that of the human eye, the corresponding image is obtained by the image acquisition device, and then the corresponding feature information is extracted, and the image information such as the distribution, brightness, and color of the pixel is converted into a digital signal, and then transmitted to the calculator by a transmission device similar to a human nerve to process the data with a specific algorithm to ignite the tremor, and finally achieve the recognition target, obtain information, etc.

Difference Between Machine Vision and Human Vision

The process of acquiring images is much the same as that of machine vision and human vision. The core of machine vision is based on a large number of artificial intelligence based on the logic of judgment, through a large number of identical ** to obtain pixels, and then analyze the data, and then by simple logic judgment to determine what the obtained image is. So sometimes there are some errors in the machine, such as the machine may recognize the pineapple as a zebra.

This is because after a huge amount of data processing, the feature results presented by their images can be extremely similar. Therefore, machine vision, as a branch of artificial intelligence, like artificial intelligence, needs to be advanced by algorithms.

At present, machine vision has long been deeply embedded in our lives, when you take out your mobile phone every day to scan *** payment, your mobile phone is "observing" the world; When you swipe your face to pass the access control or punch in with your face, the machine is also "looking" at you. In fact, machine vision can not only do simple work, it is also widely used in high-precision surgery, autonomous driving and other links. (Liu Yilian).

Supervisor: Yu Han, Associate Professor, School of Economics and Management, Communication University of China.

Expert: Cao Miaoyan, professor of the School of Mechanical Engineering, Yanshan University

According to different application scenarios, robots can be divided into cover ()a, industrial robots and service robots.

b. Entertainment robot and utility robot parsley.

c. Sweeping robot and piano robot.

d. Learning robots and housekeeping robots.

Correct Cheats Pure Answer: a