DL Based Felis Cetus Classification Using CNN And Logistic Regression
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
Related Projects
Paper Publishing
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