Android Facial Expression App
Objective
The main aim of facial expression detection is to detect customer satisfaction on the user's face which can give accurate results to the organization. And there is another thing also here we are implementing this concept to reduce the human efforts to give the customer service satisfaction.
Abstract
There is a mixed opportunity to get accurate customer reviews on customer service reviews. Sometimes customers agree to a service-based review. And users almost never pay attention to giving a manual review. Facial expression recognition is an important part of human emotion recognition, which is widely used in human-computer interaction, pattern recognition, image understanding, machine vision and other fields.
Recent years, it has gradually become a hot research. However, different people have different ways of expressing their emotions, and under the influence of brightness, background and other factors, there are some difficulties in facial expression recognition. In this first time, we are going to investigate how recognition and detection of each basic expression category (happiness, sadness, fear, disgust, anger, sadness and surprise) changes.
We recognize this application using Tensor Flow. Tensor Flow is an open-source machine learning technique for research and development areas. Tensor Flow offers APIs for beginners and experts to develop for desktop, mobile, web, and cloud. Here we are using Tensor Flow library to capture and identify the images of a different types of fruits.
Keywords: CNN, Camera, Facial Expression Recognition.
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
- Real time application scenario.
- About ML
- About ML Algorithms.
- How CNN can work
- What is the CNN Architecture?
- How ML model can integrate with android application.
- Android architecture.
- Basic about java
- Basic about MySQL
- Knowledge about server side programming
- Difference between client side and server side programming language.
- Knowledge about server
- Knowledge about database and queries.
- Knowledge about Volley API
- How to communicate with API
- How API Communicate with Server
- What are Packages and dependencies regarding the app?
- What are various versions of android app and android operating system
- About Android studio.
- Client side validation
- Server side validation
- Difference between client side validations
- Different Debugging Technique’s
- Deployment of app.
- About play store deployment
- What is manifest?
- About XML
- Widgets in android
- Views in android
- Layouts in android
- How to design the user Interface.\
- 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.
Demo Video
Request for Video
Related Projects
Paper Publishing
Request Call Back
Would you like to receive a free callback now?
Choose the best time for callback:
Leave your message and we will contact you as soon as possible
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.
