Abstract:
The purpose of this project is to demonstrate how any type of fruit, vegetable, or animal
can be rapidly clarified, illustrated, and given a suggested sentence that goes along with it.
Children can use a straightforward mobile application to learn the name of the fruit they
want to see. The user uploads a picture of any fruit, vegetable, or animal to the
classification area where they can see the precise names of the objects in the picture. How
users can use this application in their everyday lives and what kind of programming is
required for image classification. This presentation will conclude with a suggestion for a
live picture classification system, designed specifically to help kids expand their
knowledge. The image would be found by an image classification system, which would
then show the categorization in a text box. The concept is built upon image classification,
which is inherently very challenging to put into practice. Using a simple smartphone
application, kids may discover the name of the fruit they want to see. Any animal, plant,
or fruit may be photographed and uploaded to the category area, where users can see the
precise names of the objects in the picture. How to use this application in everyday life
and what kind of programming is required for photo classification. This talk will conclude
with a suggestion for a live picture classification system designed specifically to help kids
build their knowledge. Locating the image and displaying the classification in a text box
are two examples of an image categorization approach. The concept is built on the
classification of images, which is inherently very difficult to accomplish. Because we
combined the Google Colab platform with the Google Flutter mobile application and the
Google Dart language, we will employ the most well-known SDK (Software Development
Kit) MLKIT (MLKIT digital ink recognition and google MLKIT picture labeling) for the
project's advancement. An Android app will be released for the project.
