Hikvision released a technology report about the benefits of deep learning to the security industry.
With increased data volume for video surveillance, the deep learning algorithm becomes even more critical with its ability to process large amounts of data more quickly and accurately than traditional algorithms.
“Traditional intelligent algorithms generally use shallow learning models to handle situations with large amounts of data in complex classifications. The analysis results are far from ideal,” according to the report. Recognition of humans or detailed analysis of objects such as vehicle designs and logos requires more complex intelligence and more effective processing of big data.
The report also highlights why deep learning was popularized in recent years, including an increase in the scale of data, computing power, and network architecture. “In the past, hardware devices were incapable of processing complex deep learning models with over a hundred layers. Today, only a few GPUs are required to achieve the same sort of computational power with even faster iteration,” according to the press release.
In the North American market, Hikvision is leading the way with deep learning surveillance technology advances. "Our goal is to lead the way with deep learning products that provide end-users with the most reliable and accurate video content analysis,” said Jeffrey He, president of Hikvision USA, Inc. and Hikvision Canada, Inc. in an interview with leading security publications SecurityInfoWatch.com and SD&I. “Hikvision’s new DeepinView security camera series and DeepinMind NVR series of products apply deep learning algorithms to deliver some of the most accurate video analytics in the market today,” He added.
To read the entire deep learning technology report, click here.