TatevKaren/convolutional-neural-network-image_recognition_case_study

Computer Vision Case Study in image recognition to classify an image to a binary class, based on Convolutional Neural Networks (CNN), with TensorFlow and Keras in Python, to identify from an image whether it is an image of a dog or cat. (Includes: Data, Case Study Paper, Code)

30
/ 100
Emerging

This project offers a comprehensive case study for developers looking to build image classification models. It demonstrates how to train a Convolutional Neural Network to distinguish between cat and dog images, taking image files as input and outputting a binary classification (cat or dog). It's ideal for those learning or implementing basic image recognition in their applications.

No commits in the last 6 months.

Use this if you are a software developer or data scientist looking for a clear, documented example of setting up and training a CNN for binary image classification.

Not ideal if you are a non-technical user seeking a ready-to-use application to classify images without writing code.

image classification computer vision deep learning machine learning development AI model training
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 16 / 25

How are scores calculated?

Stars

21

Forks

6

Language

Python

License

Last pushed

Apr 18, 2022

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/TatevKaren/convolutional-neural-network-image_recognition_case_study"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.