What is deep learning?
First, what is the relationship between artificial intelligence and deep learning? The real part of artificial intelligence is deep learning. Because the previous artificial intelligence really cannot be used in many situations, the intelligence of human hands to design a thing is more difficult to surpass people. With deep learning, you can turn this process into a data-driven process: When a certain amount of data and parameters are large, the machine may do more than humanity in doing this. Many of the productized products that come out of the real world are made through deep learning. There are many successful cases of deep learning, one is in the field of speech recognition, and the other is probably more in visual aspects. We can see a lot of new achievements in computer vision.
What exactly does deep learning actually do? In fact, what it does abstract is relatively simple. It is doing a regression from X to Y. The person says that the mapping from A to B - you give it a Input, how does it give a corresponding output? The special place is deep learning to do this thing very well. There were also other algorithms that could have been done before, but it was just that people couldn’t do it. Now, deep learning has done its best.
For example, if you give a face photo, it will give you the name of the person; give the shape of an object, it can tell you what it is; give a car driving scene, it can give you output Where the car should turn; to a chess game, it can figure out what to do next; give a medical image, it can help you determine what the disease is ... ... is actually such a process. Do not imagine that artificial intelligence can surpass humanity and can control humans. These are the so-called "Hollywood artificial intelligence" or artificial intelligence in imagination. The real artificial intelligence is actually doing such a simple thing at this stage, of course. This simple matter is actually very simple.
Deep learning breakthrough?
In recent years, deep learning has indeed made major breakthroughs in academia and industry. The first breakthrough was in speech recognition. After the great success of speech recognition, deep learning followed another major breakthrough in visual aspects. Then artificial intelligence has also made some major breakthroughs in the field of automatic driving. Now more popular is medical imaging, with the help of artificial intelligence for diagnosis.
There are three core elements of deep learning: the design of learning algorithms, the brain you design is not smart enough, you need high-performance computing skills to train a large network, and you must have big data.
Application of "deep learning + security"
At present, the main research areas of deep learning are in speech recognition and vision, and deep learning is applied in all directions, and different technological innovations can be made in different fields. For the security industry that has mastered many video image resources, the combination of deep learning and security has a high degree of fit, namely analysis of images and videos, including:
——In terms of image analysis, such as familiar face recognition, text recognition, and large-scale image classification, deep learning has greatly improved the accuracy of complex task classification, and has greatly improved the accuracy of image recognition, speech recognition, and semantic understanding. .
- In terms of face, face detection, face key point location, ID comparison, clustering, face attributes, and live detection can be achieved. In terms of intelligent monitoring, it can be used as a structural study of video of people, motor vehicles, and non-motor vehicles.
- In terms of words, the identification of small tickets, the identification of credit cards, and the identification of license plates are all done by deep learning algorithms. At the same time, in terms of image processing, HDR, various intelligent filter designs in de-fogging, super-resolution, de-jittering, de-blurring, and deep-learning algorithms are used.
Some people say that deep learning technology can be described as a "subversive force" in the security industry, which greatly promotes the development of intelligent security. Compared with traditional intelligent algorithms in the past, deep learning is more “smart†in solving video structuring and face recognition. Such as video structuring, the people inside the video, motor vehicles, non-motor vehicles and their characteristics are detected and automatically marked out, so that the entire video becomes a document and can be documented; human faces Dispatch control system has been deployed in real time in many cities, and there are people arrested more than 100 meters away. One hundred meters away they see a target approaching and face recognition.
With the breakthrough of deep learning algorithms, intelligent analysis technologies such as target recognition, object detection, scene segmentation, and character and vehicle attribute analysis have made breakthrough progress.
At this stage, not only the security industry, more and more industries and companies are exploring in the field of deep learning. Of course, we also expect that under the influence of deep learning or even artificial intelligence and the innovation of various security manufacturers, more intelligent security products can be quickly applied to the ground to improve the working efficiency of urban security systems!
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