Creating An Artificial Intelligence-Powered Image Classification Model For Specially Abled Persons
Kandula Srikanth, Munni Venuthurumilli, Nune Vl Manaswini, Meduri V N S S R K Sai Somayajulu · 2023
This article describes how to use Python’s Keras deep learning package to build an Artificial Intelligence-powered image classification model. Speech, text, and other types of input are transformed into machine-readable form by the system using natural language processing (NLP) and speech recognition technology. Other assistive technologies can be adapted to and used with the system. The purpose of this study is to show how straightforward and simple it is to use Keras to create an accurate picture categorization model. Convolutional neural network (CNN) architecture, a kind of deep learning model best suited for image classification tasks, is built first in the procedure. Following that, the model is assembled and trained on a sizable dataset, where it discovers patterns and features in the photos. The model is tested and evaluated on fresh data after training to ensure accuracy. The outcomes demonstrate that Keras can efficiently and accurately construct an AI-powered picture classification model, making it a useful tool for resolving practical computer vision issues. This demonstrates the capabilities of AI in this area and offers a thorough manual for people wishing to create their own picture classification models using Keras.