**9. Conclusions**

**8.2 Unsupervised ANN model**

*Output summary of CNN model.*

**Figure 13.**

**Figure 14.**

**98**

*Pictorial output of SOM model.*

A simple unsupervised ANN model was developed for the colour quantization of

Two different images of houses were selected for colour quantization by the SOM model. Separate tests were conducted with each image keeping the same model conditions. In each test, the developed SOM model reduced the distinct colours of the image, and another image was developed. This technique helped the model to learn the colours in the image and then use the same colours to reconstruct

an image, using Python, and Self-Organising Maps (SOM) methodology was

that image. The pictorial views for each output are shown in **Figure 14**.

adopted. SOM is basically used for feature detection.

*Dynamic Data Assimilation - Beating the Uncertainties*

Operation of the ANN model is the simulation of the human brain, and they fall under the knowledge domain of AI. The popularity of ANN models were increased in the early 1990s, and many studies have been done since. The basic ANN model has three main layers, and the main process is performed in the middle layer known as the hidden layer. The output of the ANN model is very much dependent on the characteristics and function it carries under the hidden layer. Among the feedforward and feedback networks, the latter one propagates the error unless it became minimum for more effective results. The ANN models can perform supervised learning as well as unsupervised learning depending upon the task. The DL algorithms are very much popular among researchers because of effective outputs with large data. CNN and RNN are the two renown deep networks, and they have been used for various applications. Output accuracy of the ANN models is very much dependent on the number of hidden layers and the number of epochs.

In this era of automation, the AI plays an important role, and most of the daily use applications are based on the architecture of ANN models. This ANN technology, combined with other advanced and AI knowledge areas, is making life easier in almost every domain. This evolution of DNN models has led to the creation of Sophia the Robot (Hanson Robotics); the journey is on-going.

#### **Acknowledgements**

We will like to acknowledge UTP.

## **Conflict of interest**

There is no conflict of interest.
