Questions Technology

How transferable are the features in deep neural networks?

Airtract

Madhu Mannen

Think Big

The popularity of machine learning and artificial intelligence has been on the rise in the popularity scale in the global market. The introduction of these applications has made the overall aspect of managing the operations of a business organization much easier. Now the concept of deep neural networking is capturing the attention of IT professionals as it can be used in an effective manner to solve issues related to computer vision, speech recognition, images based on the medical field and its analysis.

The operation of a Deep Neural Network is a little complicated. DNN or Deep Neural Network uses various layers to register different mathematical values and converts this input into an output value which can be displayed on a pixel screen. As the name already suggests, Neural Networks is directly connected with the operations of the human brain. The neurons which specific values are linked together to form a chain of networks which give rise to an image which can be interpreted by the brain.

Let put this in simple terms so that everyone can get a clear idea of what Neural Networks actually stands for by dissecting an example of DNN analysis. A Neural Network consists of several neurons, and as mentioned before, each neuron has the ability to hold or carry a particular number which ranges anywhere from a zero to one [0-1]. Every number denotes a specific color which in turn is broadcasted on the pixel screen. In very 28 by 28-pixel image, there are a total of 784 neurons that have the capability to hold a value which is represented with shades of black and white. The black pixels are valued at zero whereas the white pixels are denoted with a value of 1.

Based on the brightness of a particular neuron, our brain is able to analyze the pixel image and identify the said value which is being portrayed. This is how information is transferred with the help of Deep Neural Networks. The DNN network tries to replicate how the human brain analyses and recognizes patterns and date and it tries to copy that in the form of a machine learning algorithm. This is how the transfer feature of Deep Neural Network operates, and it seems to work every time. The message conveyed is quick and efficient and is gaining a lot of popularity in the present market scenario due to its wide application and use.

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