Fraudsters collaborate, but most banks still detect fraud alone. This imbalance has defined fraud prevention for years. Now ...

src/ # Core system ├── monitoring/ # Resource collection ├── preprocessing/ # Data cleaning & feature engineering ├── anomaly_detection/ # ML model (Isolation Forest) ├── adaptive_engine/ # Decision ...

Abstract: Unsupervised medical anomaly detection aims to identify abnormal images by training exclusively on normal samples, thereby enabling the detection of disease related irregularities without ...

School of Computer Science, Nanjing University of Information Science and Technology, Nanjing, China. The rapid expansion of the Internet of Things (IoT), cloud computing, and remote work ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

A preliminary report by the Hong Kong Air Accident Investigation Authority (AAIA) into the runway excursion of an AirACT Boeing 747-400F points to asymmetric thrust during landing as a key factor ...

Abstract: Anomaly detection is a key technology in quality control for automated production lines. Currently, 2D-based anomaly detection methods fail to identify geometric structure anomalies in ...

ABSTRACT: Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex ...

Cybersecurity professionals recognize that enterprise networks are prime targets for dark web risks such as ransomware, unauthorized insider activity, and data exfiltration. What’s less obvious is ...