Classification of Artifacts Using machine learning

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  accuracy

Inspiration

Since classification of artifacts is usually performed by visual inspection, techniques from computer vision and machine learning can be applied in order to develop such tools.

What it does

The Project titled classification of artifacts based on machine learning describes the classification of historical artifacts based on machine learning algorithms.

How we built it

The model is trained using CNN (Convolution Neural network) using VGG19 transfer learning by adding the custom layers on three different categories namely Basket, Coin and Figure.

Challenges we ran into

Very tricky to find dataset and then feed it to the model.

Accomplishments that we're proud of

Completed the project with 80 to 90% accuracy

What we learned

Tackle a problem with pressure

What's next for Classification of Artifacts Using machine learning

Image regeneration with the help of mahine learning

Built With

• flask
• keras
• numpy
• pickle
• python