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# Neural_Networks_Project
The name of the project is the following: Augmenting Convolutional Networks with Attention-based Aggregation for Breast Cancer Detection.
-
-This is the final project for the course of Neural Networks 2021/2022 at Sapienza University of Rome.
-
+This is the final project for the course of Neural Networks 2021/2022 held by professors Aurelio Uncini and Danilo Comminiello, at Sapienza University of Rome.
>Student: Filippo Betello Mat: `1835108`;
>
>Student: Federico Carmignani Mat: `1845479`;
## 📝 Assignment
-
-1. Reimplement the network architecture in the Paper [Link 🔗](https://arxiv.org/abs/2112.13692) for Image Classification on CIFAR10.
+1. Reimplement the network architecture in the [Paper](https://arxiv.org/abs/2112.13692) for Image Classification on CIFAR10.
2. Apply this innovative architecture to Breast Cancer Detection.
## 💾 Dataset
+- [CIFAR10](https://www.cs.toronto.edu/~kriz/cifar.html)
+- Kaggle Dataset for Breast Histopathology Images [Link 🔗](https://www.kaggle.com/datasets/paultimothymooney/breast-histopathology-images)
-- CIFAR10 [Link 🔗](https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz)
-
-## 📜 Report
-
-- power point presentation ()
-- paper [Link 🔗]()
+## 📜 Results
+For CIFAR10 dataset results are very good:
+
+For the Kaggle dataset we obtained 87.95% of accuracy:
+
+This work can be found in the [PDF report](./Neural_network_project_BETELLO_CARMIGNANI.pdf) and in the [PPT] presentation(./PPT_NN.pptx).>br>
- In these files you can read more about the code and the result of the project.
-
-## 💯 Final score:
-
-Score: `30L`
+We noticed that in this last image we couldn't know if the attention map created was highlighting the correct patch of the image or not, so we decided to use another [dataset](https://wiki.cancerimagingarchive.net/display/Public/CBIS-DDSM) where the ground trouth were provided:
+
+This last step is currently under developing by professor Comminiello and one of his PhD students. [Here](./NN_last_report.pdf) you can find an abstract.
## 🙋 Info
-
-for any doubt or clarification contact us on:
-
-- send an email at: carmignani.1845479@studenti.uniroma1.it or betello.1835108@studenti.uniroma1.it
+For any doubt or clarification send an email at: carmignani.1845479@studenti.uniroma1.it or betello.1835108@studenti.uniroma1.it.
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