Image Classification Using Inceptionv3 and Co...

Image Classification Using Inceptionv3 and Convolutional Neural Networks

Author Name : Dr. T Vijaya Saradhi, B. Ramadevi, K. Archana, K. Rajeshwari

ABSTRACT

In today world the image classification have won  the lot of attention. Image classification is used  to classify image  by using CNN . In our project we have used inception V3 model.  CNN is a image classification model and it is used for image processing .In our project we have used one of the CNN model which is inception V3 is the advance of the V1 and V2 model . CNN is having multiple layers which will lead to confusion. to avoid the confusion we will be using inception V3 model. Inception  V1 model is used for filtering. By using inception V3 model it will make the layers parallel and it will further filter the layers.The layers will be parallel so that no confusion will be occurring between layers  inception V3 model is very effective and and it is less cost compared to other models . In image classification the content can also be classified in our project  we have considered  a data set from the kaggle and the data set contains 7000+ images and the data set is trained and the images classified according to the classes and the resultant will be the image along with the label . Example if we consider a group of images and if train the model to identify the  images of the animals the model will be able to identify the image of the animal and it will be tested. Other project God dam got got the accuracy of 94 percentage and in the future that the models will be trained further for the very large datasets. CNN is one of the best models for image processing and image classification. Image classification and detection is done in our model the the images of the mountains streets and furthermore are classified and detected. Classification and detection is done in our project using the inception V3 model.