ML Based Body Mass Index Detection Using Facial Recognition
Objective
The main objective of this to predict the BMI of a person by giving the image as input using Machine Learning algorithms.
Abstract
Abstract: Body mass index (BMI) is used widely as an indicator in general health. Determination of BMI using non-intrusive measurements are of interest and recent advancements in the availability of digital imaging sensors have paved the way for performing quick and automatic measurements. In this work, we consider automatic computation of BMI using the machine learning algorithms. We are considering the face image dataset where we are extracting the embedding from the face images and then training with the linear regression and random forest algorithms. Once after training we can test by giving the face input image.
Keywords: BMI, Machine Learning, Linear regression, random forest, face 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
H/W Specifications:
- Processor:
I3/Intel Processor
- RAM: 8GB (min)
- Hard Disk : 128 GB
S/W Specifications:
- Operating System: Windows 10
- Server-side Script : Python 3.6
- IDE : Jupyter Notebook/Google Colab
- Libraries Used: Numpy, face_recognition, keras.
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 Machine Learning techniques
· Working of Linear regression algorithm
· Working of random forest algorithm
· Working of face regonnition
· Building of model creations
· Scope of project
· Applications of the project
· About Python language
· Use of Data Science
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