Ganz Security

What is Deep Learning?

August 2, 2021


What is it?

Deep learning is a subcategory of machine learning. It is a neural network with multiple layers. These neural networks attempt to mimic the behavior of the human brain, allowing it to “learn” (hence the name “deep learning”) from large amounts of data. While a neural network with a single layer can still make approximate predictions, added hidden layers can help to optimize and refine the layers for accuracy.

Deep learning drives many artificial intelligence (AI) applications such as our AI Box and other technologies that improve automation. Deep learning technology lies behind everyday products and services (such as digital assistants like Siri and Alexa, and smart home features like room-mapping automatic vacuums) as well as up-and-coming technologies like self-driving cars.

How does it work?

In a nutshell, deep learning consists of three layers. According to  Free Code Camp, like animals, the AI brain has neurons that are interconnected. The neurons are grouped into three different types of layers:

  1. Input Layer–receives input data
  2. Hidden Layer(s)– performs mathematical computations on our inputs
  3. Output Layer–returns the output data

The “Deep” in Deep Learning refers to having more than one hidden layer. Each neuron has an Activation Function, to standardize the output from the neuron. Once a set of input data has passed through all the layers of the neural network, it returns the output data through the output layer.

How can it help me?

Within the security industry, deep learning is a cutting-edge solution for current and future security systems. For instance, our AI Box uses deep learning and analysis to recognize and classify detected objects, including people, vehicles, motorcycles, bicycles, and more. When there is a critical activity such as illegal parking, trespassing, or even fallen persons, the AI Box sends alerts to the user or initiates an action. Click here for a full list of the AI Box features.

To simplify, how AI impacts event recognition:

  1. In standard non-AI cameras, events can be triggered by either motion, zone, or trip line
    1. An object is detected generating motion, passed through the zone, or has crossed the line
    2. There is nothing to classify the nature of the object that triggered the event
  2. With AI assistance for the camera, a filter can be applied to classify the nature of the object
    1. AI can determine a person or a vehicle that can generate the motion, has passed through the zone, or has crossed the line
    2. AI can then refer to AI Logic (Machine Learning), filter out the person, and trigger only on an object classified as a vehicle; now only a vehicle can trigger an alarm state
  3. AI allows filtering of event generation, based on recognition of an object’s classification
    1. The trigger occurs only upon specific objects based on their classification

In closing, deep learning is a formidable, cutting-edge tool that is shaping the way of future technology. 

To learn about how deep learning can help you better secure your institution, register for our free webinar here.


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