DL Based Felis Cetus Classification Using CNN And Logistic Regression

Project Code :TCMAPY446

Objective

The main objective of this project is to classify different cat breeds using deep learning based CNN algorithm.

Abstract

The automatic classification of animal images is an onerous task due to the challenging image conditions, especially when it comes to animal breeds. In this paper, we built a model based on Convolutional Neural Network (CNN) of deep learning that which can classify the cat breeds. We are mainly considering the CNN based transfer learning that which is used to train the dataset of cat breed and based on this training we can classify the cat breeds.

Keywords: Cat Breed, Classification, Deep Learning, CNN

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

H/W Configuration:

· Processor : I3/Intel Processor

· Hard Disk : 160GB

· RAM : 8Gb

S/W Configuration:

· Operating System : Windows 7/8/10 .

· Server side Script : HTML, CSS & JS.

· IDE : Pycharm.

· Libraries Used : Numpy, IO, OS, Flask, keras.

· Technology : Python 3.6+.

Learning Outcomes

Practical exposure to

Hardware and software tools
Solution providing for real time problems
Working with team/individual
Work on creative ideas

Testing techniques
Error correction mechanisms
What type of technology versions is used?
Working of Tensor Flow
Implementation of Deep Learning techniques
Working of CNN algorithm
Working of Transfer Learning
Working of MobileNet algorithm
Building of model creations
Scope of project
Applications of the project
About Python language
About Deep Learning Frameworks
Use of Data Science

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