Deep Learning Based Food Classification

Project Code :TCMAPY455

Objective

The main objective of this to classify the images of food using the Transfer Learning based Convolution Neural Network (CNN) of deep learning. Here, we mainly explore the problem of food classification.

Abstract

Food dominate across social media platforms and drive restaurant selection and travel, but are still fairly unorganized due to the sheer volume of images. Utilized correctly, food image classification can improve food experiences across the board, such as to recommend dishes and new eateries, improve cuisine lookup, and help people make the right food choices for their diets. In this paper, we explore the problem of food image classification through training convolutional neural networks. Here we are using Transfer Learning based Convolution Neural Network (CNN) of deep learning that which classifies the food accurately.


Keywords: Food Classification, deep learning, CNN, Transfer Learning

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

HARDWARE SPECIFICATIONS:

  • Processor: I3/Intel
  • Processor RAM: 8GB (min)
  • Hard Disk: 128 GB

SOFTWARE SPECIFICATIONS:

  • Operating System: Windows 7+
  • Server-side Script: Python 3.6+
  • IDE: PyCharm
  • Libraries Used: Numpy, IO, OS, Flask.

Learning Outcomes


  •          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
  •          Building of model creations
  •          Scope of project
  •          Applications of the project
  •          About Python language
  •          About Deep Learning Frameworks
  •          Use of Data Science
  •          Practical exposure to
    •          Hardware and software tools
    •          Solution providing for real-time problems
    •          Working with team/individual
    •          Work on creative ideas

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