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International Journal of Scientific Research in Computer Science, Engineering and Information Technology
ISSN : 2456-3307 (www.ijsrcseit.com)
doi : https://doi.org/10.32628/CSEIT251445
446
Dog Breed Prediction Using Deep Learning and E-commerce
Abhinav Rajhans
1
, Rajan Gupta
1
, Satyam Dubey
1
, Piyush Dave
1
, Prof. Aabha Patil
2
1
Department of Computer Engineering, Shree L.R Tiwari College of Engineering Mumbai, Maharashtra, India
2
Assistant Professor, Department of Computer Engineering, Shree L.R Tiwari College of Engineering Mumbai,
Maharashtra, India
A R T I C L E I N F O A B S T R A C T
Article History:
Accepted: 01 April 2023
Published: 21 April 2023
This project uses computer vision and machine learning techniques to
predict dog breeds from photographs and provides a trustworthy and
efficient e-commerce platform for dogs. With the help of various machine
learning models such as convolutional neural networks, our model gives
the correct breed 90% of the time. Apart from that, our web application
also provides an e-commerce platform for buying of dogs.
Keywords: Computer Vision, Machine Learning, E-Commerce
Publication Issue
Volume 10, Issue 2
March-April-2023
Page Number
446-451
I. INTRODUCTION
Artificial intelligence enables the machine to achieve
human level intelligence. Machine learning allows
the machine to extract useful information from any
data. Deep learning is a further subfield of ML that
utilizes artificial neural networks inspired by human
brain. These Neural Networks can grasp and
recognize patterns in data and develop models,
without being explicitly instructed on how to solve a
problem. Using Deep Learning we can detect many
things such as objects, animals, humans etc. There are
many algorithms for image processing such as A
Convolutional Neural Network. Convolutional Neural
Networks (CNNs) are a popular class of deep learning
algorithms that are specifically designed for
processing visual data such as images and videos.
Using Such Deep Learning Algorithms. [1]
The aim of this project is to classify images of dogs
into their respective breeds and build a trustworthy
and efficient E-commerce for buying and selling of
Dogs. Classifying dog breeds from images is a fine-
grained task that is complicated by the fact that many
breeds share similar body features and overall
structure and it is challenging due to the diversity
among breeds and the high level of variation within
breeds in terms of size, shape, and colour. This
difficulty is further compounded by the variations in
lighting and positioning of dogs within the dataset
used for this project, which includes images of dogs
from the same breed but in different styles.
However, the techniques used to address the
challenge of classifying dog breeds from images could
be beneficial in identifying breeds of cats and horses,
as well as various species of birds and plants.
Moreover, the methods could potentially be extended
to classify models of cars or other objects. The ability
to predict dog breeds from images could also benefit