ExeRay AI detects malicious Windows executables using ML. Analyzes entropy, imports, and metadata for rapid classification, aiding incident response. Built with Python and scikit-learn.

Extracting features from URLs to build a data set for machine learning. The purpose is to find a machine learning model to predict phishing URLs, which are targeted to the Brazilian population.

🌸 Breast epithelium segmentation through IHC-guided supervision

Official implementation of the paper: "REGroup: Rank-aggregating Ensemble of Generative Classifiers for Robust Predictions", IEEE WACV, 2022

Using Mammography and Histopathology (ResNet for classification and UNet for detection)

Classification of Benign and Malignant Breast Cancer using Supervised Machine Learning Algorithm Logistic Regression

Esophagus Granular Cell Tumor - Özofagus Granüler Hücreli Tümör

Benign Prostate Hyperplasia - Benign Prostat Hiperplazisi

Reactive atypia in an ulcerated colon polyp - Ülsere Kolon Polibinde Reaktif Atipi

Liver Hemangioma - Karaciğer Hemangioma

Gallbladder Rokitansky-Aschoff Sinus - Safra Kesesi Rokitansky-Aschoff Sinus

Endometriosis - Endometriozis

Setup IPFS and Host Simple Benign HTML and Executable

Morphea - Morfea

Exostosis: Osteochondroma - Ekzostoz: Osteokondrom

Collect and download benign Windows PE executables from marketplace sources for research and machine learning

Ochronosis - Okronozis

Pancreas Solid Pseudopapillary Neoplasm - Pankreas Solid Psödopapiller Neoplazm