This project implements an Bidirectional LSTM Autoencoder-based anomaly detection system for CubeSat telemetry monitoring. It processes multi-channel satellite telemetry data in real-time, detects ...
The vulnerability is tracked as CVE-2025-12058 and it can be exploited for arbitrary file loading and conducting SSRF attacks. A vulnerability in the open source library Keras could allow attackers to ...
Image Denoising with Autoencoders in R (University Project) Built a convolutional autoencoder in R using Keras/TensorFlow to perform image denoising on MNIST and CIFAR-10 datasets with varying levels ...
Abstract: Anomaly detection problem for time series refers to finding outlier data points relative to some standard or usual signal. A price action that contradicts the expected movement of the stock ...
Sparse autoencoders are central tools in analyzing how large language models function internally. Translating complex internal states into interpretable components allows researchers to break down ...
1 College of Information Engineering, Xinchuang Software Industry Base, Yancheng Teachers University, Yancheng, China. 2 Yancheng Agricultural College, Yancheng, China. Convolutional auto-encoders ...
Abstract: Through deep learning Autoencoder Decoders, it is possible to clean noisy or damaged image data received from satellites. Two models with a PSNR of 25.6 dB and 25.54 dB were generated using ...
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