Over the past five years, significant advances in computing power have sparked an AI revolution, prompting tech giants such as Alphabet (Google's parent company), Amazon, Apple, Facebook, and Microsoft to race into this field. Public interest in AI reached a new peak, particularly following the high-profile matches between AI-powered robots and human players last year. While the development of AI dates back more than six decades, the field experienced several periods of stagnation due to technological limitations; it was the emergence of deep learning that reignited the AI boom.

Deep Learning Reignites AI; Security Emerges as a Key Sector

What is deep learning?

Deep learning is a subset of machine learning—a method that enables computers to become more intelligent by learning from examples representing the world around us or specific aspects of it. Among the various machine learning methods, deep learning stands out because it draws inspiration from research into the human brain. It aims to teach computers to learn multiple levels of abstraction and representation, a capability that likely accounts for the remarkable success of these systems.

Why has the security industry become a focal point for deep learning?

The security sector generates massive amounts of data continuously. In the last two years, AI technology has imbued this data with new significance, helping to solve a wider range of problems within this traditional industry.

As a natural training ground and application environment for AI technology, the security industry has an urgent need for practical AI implementation. Given its inherent characteristics, the sector has invested heavily in the AI market. Keenly aware of market trends, major equipment and solution providers have moved quickly to establish a presence; leveraging their deep industry experience, they have achieved impressive results in practical applications. Notably, breakthroughs in deep learning have been particularly significant, serving as a key driver in the rapid development of AI.

Deep learning research focuses primarily on speech recognition and computer vision. Applying deep learning across various directions enables technological innovation in diverse fields. For the security industry—which possesses vast video and image resources—the integration of deep learning offers a highly synergistic fit, particularly regarding image and video analysis, including:

——In the realm of image analysis—covering familiar applications such as facial recognition, text recognition, and large-scale image classification—deep learning has dramatically improved classification accuracy for complex tasks, leading to significant gains in the precision of image recognition, speech recognition, and semantic understanding. ——Regarding facial analysis, capabilities include face detection, facial landmark localization, ID card verification, clustering, attribute analysis, and liveness detection. In the realm of intelligent surveillance, video structuring—analyzing people, motor vehicles, and non-motorized vehicles—can be performed.

——Regarding text processing, tasks such as recognizing receipts, credit cards, and license plates are all handled by deep learning algorithms. Similarly, image processing functions—including dehazing, super-resolution, stabilization, deblurring, HDR processing, and the design of various intelligent filters—also utilize deep learning algorithms.

In the security industry, deep learning applications primarily focus on four key areas: human analysis (facial recognition and human feature extraction), vehicle analysis (vehicle recognition and feature extraction), behavior analysis (target tracking/detection and anomalous behavior analysis), and image analysis (video quality diagnosis and video summarization). [Details: http://www.afzhan.com/news/detail/53981.html] Breakthroughs in deep learning algorithms have driven significant progress in intelligent analysis technologies, such as target recognition, object detection, scene segmentation, and attribute analysis for people and vehicles.

The "AI + Security" Trend

According to the report *Analysis of Development Prospects and Investment Strategy Planning for China's "Internet + Security" Industry* by the Qianzhan Industry Research Institute, the demand for security solutions has steadily risen in recent years. my country's security industry market size grew from 235 billion RMB in 2010 to 540 billion RMB in 2016, representing a compound annual growth rate (CAGR) of 15%.

Notably, compared to traditional security methods, next-generation security technologies are leveraging artificial intelligence, cloud computing, big data, the Internet of Things (IoT), and mobile internet to achieve rapid, diversified growth. The "AI + Security" trend is ushering in a "smarter" era of security.

According to the *Development Plan for China's Security Industry during the "13th Five-Year Plan" Period (2016–2020)* released by the China Security & Protection Industry Association (CSPIA), the industry is set to undergo a transformation toward greater scale, automation, and intelligence during this period. By 2020, the total revenue of security enterprises is projected to reach approximately 800 billion RMB, with an annual growth rate exceeding 10%. "Over the next four to five years, the security industry will enter an era of rapid AI development," stated Yan Xiaqing, Vice President of Uniview, a domestic security company. He noted that the industry largely achieved adaptation to scenario-specific intelligence by 2016; the 2017–2018 period marks the transition to a deep-learning-based AI phase; and the years 2019–2020 will see a full-scale entry into the stage of digital intelligence. Ultimately, following the digital intelligence phase, AI in the security sector will seamlessly integrate with comprehensive big data platforms across the entire IT landscape, ushering the security industry into the intelligent era.

Beyond garnering an enthusiastic response from industry giants, the "AI + Security" sector has also received policy support at the national level.