Image Classification Using Machine Learning and Deep Learning Model

EasyChair Preprint 8118

Abstract

A deep neural network (DNN) is an artificial neural network (ANN) with multiple layers between the input and output layers. Deeper neural networks are more difficult to train Many problems in computer vision were saturating on their accuracy before a decade. However, with the rise of deep learning techniques, the accuracy of these problems drastically improved. One of the major problems was that of image classification, which is defined as predicting the class of the image. Cat and Dog image classification is one such example of where the images of cat and dog are classified. This paper aims to incorporate state-of-art technique for object detection with the goal of achieving high accuracy. A convolutional neural network has been built for the image classification task.

Keyphrases: CAT, Classification, Pooling, ReLU, Softmax, dog, image, machine learning

@booklet{EasyChair:8118,
  author    = {K R Sinchana and Suman R Kunte},
  title     = {Image Classification Using Machine Learning and Deep Learning Model},
  howpublished = {EasyChair Preprint 8118},
  year      = {EasyChair, 2022}}