- implementing a simple single neural network using sigmoid and tanh and comparing results
- Implementing a MLP , based on differenet datasets
- Using K-means algorithm in blobs dataset and image size reduction
- Implementing RBFN
As a final project of this course we were asked to built a network which must have ability to detect the face area and then recognising the person. We used 14 Celebs dataset on Kaggle. We used densenet and then Resnet as our base model and changed the last layer in different ways to fine-tune the model for our specific problem. We experiment with different combinations of the last layer and choose the best one based on the validation accuracy. And finally to get the smaller and more efficient network we used MobileNet as our based model. Here are summaries of diffrent model we used.
- ResNet
- DenseNet
- MobileNet
- Number of Parameter and Size of Model
- Reyhaneh Ahani
- Mahdiye Sadat Benis
- Samira Saljoghi
- Fatemeh Rafiee