Animal Breed Classification Using Deep Learning

Project Code :TCMAPY670

Objective

The main objective of this project is to classify the breed of the animal using deep learning techniques.

Abstract

Primates are very significant in various environment functions as well as in human evolution, cultures, and many religions in society. Out of more than 500 primate species over 60% of primate species are extinct because of various reasons such as hunting, habitat loss human activities, etc. It is our responsibility to safeguard the primate breeds once again introducing primates into their natural surroundings. In this paper, a deep Convolutional Neural Network was trained to classify various primate breeds and predict the breed of a particular test image.   Animals breed dataset from the Kaggle data science community was used. The model was trained with different epochs, works with an accuracy on the training set and 0.7353 on the validation set with epochs 15. The trained model predicted the primate breeds accurately. These predictions are very helpful in identifying various primate breeds and protecting and safeguarding those breeds from extinction. In future this research can be extended to automate the process for identifying the primate breeds by embedding the process into IoT.

Keyword: Deep learning, animal classification, image classification, CNN, Mobilenet, image processing.

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 Specifications:

  • Processor :  I5/Intel Processor
  • RAM:  8GB (min)
  • Hard Disk :  128 GB

S/W Specifications:

  • Operating System :Windows 10
  • Server-side Script :Python 3.6
  • IDE : PyCharm, Jupyter notebook
  • Libraries Used :Numpy, IO, OS, Flask, Keras, pandas, tensorflow

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 methods

·         Building of model creations

·         Scope of project

·         Applications of the project

·         About Python language

·         About Deep Learning Frameworks

·         Use of Data Science

Demo Video

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