Paper PublishingAnimal recognition
Objective
The animal recognition project is to recognise the animals using a convolution neural network. Although various machine learning models can classify images of different animals, it remains a challenge to distinguish animal species. This is because there are certain species with a high color similarity. It is a complicated process that requires expertise even for human beings. The CNN models are efficient modern recognition methods.
Abstract
Animal species recognition and classification with CNN is expected to be helpful for various applications. However, sophisticated feature recognition is essential to classify quasi-species with similar features, such as the quasi-species of parrots that have a high color similarity.
The purpose of this project is to develop a vision-based mobile application to classify endangered animals using an advanced CNN model based on transfer learning. We acquired the images in two ways: collecting them directly from the Zoo and crawling them using the Google search.
Subsequently, we have built advanced CNN models with transfer learning and trained them using the data. Next, we convert one of the fully trained models into a file for execution on mobile devices and created the Android package files. The accuracy was measured for each of the eight CNN models.
Keywords: Recognition, CNN Model, Animal Recognition, Classification.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
SOFTWARE SPECIFICATIONS
- Operating System: Windows and Android
- SDK IDE: Android Studio 3.3
- Virtual Emulator: Nexus Pixel 2
- Programming Language: Java
- Front End: Xml
- Server scripting Language: PHP
- Database: MySQL
HARDWARE SPECIFICATIONS
- CPU type: Intel i7
- Ram size: 16 GB
- Hard disk capacity : 1TB
- Monitor type: 15 Inch color monitor
- Keyboard type: Internet keyboard
- Mobile: Android
Learning Outcomes
- About Android Studio.
- About java.
- About volley servers.
- About Fragments.
- About manifest.
- About dependencies.
- About griddle builds.
- About uses and permissions.
- About Edit texts.
- About Relative layout.
- About Linear layout.
- About image views.
- About Libraries.
- About Resource layout.
- About Activities.
- About Layouts.
- About Adapters.
- About Different types of Buttons.
- About XML code.
- About how to send notifications.
- About Views.
- About JSON objects.
- About Intents.
- About put extra params to pass the values.
- About PHP.
- About SQL.
- About Database.
- About data base tables.
- About How to store data in database.
- About CNN.
- About how to process the images.
- About how to recognize the animals.
- About how to use the CNN algorithm in the process.
- Project Development Skills:
- Problem analyzing skills.
- Problem solving skills.
- Creativity and imaginary skills.
- Programming skills.
- Deployment.
- Testing skills.
- Debugging skills.
- Project presentation skills.
- Thesis writing skills.
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Disclaimer - Takeoff Edu Group Projects, are not associated or affiliated with IEEE, in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, and not projects of or by IEEE.
