This repository contains a Jupyter notebook that demonstrates various tasks related to breast ultrasound image analysis using deep learning techniques. The notebook combines code for image segmentation, classification, compression, reconstruction, and generation.
- Image Segmentation with UNet
- Image Classification with VGG16, VGG19, EfficientNet
- Transfer Learning and Fine-tuning
- Image Compression and Reconstruction with AutoEncoder
- Image Generation with Deep Convolutional Generative Adversarial Networks (DCGAN)
The dataset used in this notebook is sourced from Breast Ultrasound Images Dataset on Kaggle.
- Image Segmentation with UNet
- Image Classification with VGG16, VGG19, EfficientNet
- Image Compression and Reconstruction with AutoEncoder
- Image Generation with DCGAN
The original code for this repository can be found at Segmentation, Classification, Autoencoder, GAN.
Feel free to explore, contribute, and use the code for your own projects, and contribute to this project!