bhavul/Caltech-101-Object-Classification

Multiple approaches tried for Object classification on Caltech 101 Dataset

27
/ 100
Experimental

This project helps computer vision researchers and students understand and perform image classification. It takes images from the Caltech 101 dataset and outputs predicted object categories, allowing users to experiment with different neural network models for identifying objects like airplanes or watches. The primary users are those learning or experimenting with deep learning for object recognition.

No commits in the last 6 months.

Use this if you are a student or researcher wanting to learn about or experiment with deep learning models for image classification on a well-known dataset.

Not ideal if you need to classify objects outside the 101 categories of the Caltech 101 dataset, or if you're looking for a production-ready object detection solution rather than a classification experiment.

image-classification computer-vision deep-learning object-recognition machine-learning-experiment
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 8 / 25
Community 15 / 25

How are scores calculated?

Stars

7

Forks

5

Language

Jupyter Notebook

License

Last pushed

Oct 21, 2020

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/bhavul/Caltech-101-Object-Classification"

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