IEEE

READ3D-Net: Residual Autoencoder and GAN-Based 3-D Convolutional Network for Anomaly Detection

Abstract: Video anomaly detection (VAD) is of great importance for a variety of real-time applications in video surveillance. Most deep learning-based anomaly detection algorithms adopt a one-class ...
GitHub

vedkumar-it/uidai-anomaly-detection

This hybrid approach achieves 94.1% accuracy while maintaining a low 2.8% false positive rate, making it suitable for production deployment in UIDAI's fraud detection pipeline. uidai-anomaly-detection ...
IEEE

Autoencoder Architectures for Low-Rate Sparse Point Cloud Geometry Coding

Abstract: Efficient compression of sparse point cloud geometry remains a critical challenge in 3D content processing, particularly for low-rate scenarios where conventional codecs struggle to maintain ...
GitHub

Anomaly Detection in Stock Prices using LSTM Autoencoder

This project shows how to find anomalies in financial time series data, specifically the stock values of Apple (AAPL), using a LSTM Autoencoder. Stock price anomalies may be a sign of major market ...