Contribute to Khalid4dev/Autoencoder-Based-Anomaly-Detection-for-Network-Intrusion-Detection development by creating an account on GitHub. Skip to content. Navigation Menu Toggle navigation. ... An ...

Autoencoders are based on neural networks, and the network consists of two parts: an encoder and a decoder. Encoder compresses the N-dimensional input (e.g. a frame of sensor data) into an ...

Both supervised ML and DL techniques are employed to explore effective anomaly detection strategies. Extensive experimentation and evaluation using metrics such as confusion ... perform better on MFCC ...

Tissue staining is a cornerstone of medical diagnostics, used to highlight cellular structures and render tissue features ...

In the realm of infrastructure maintenance, a novel approach to detecting concrete bridge damage has emerged. Researchers ...

Opinion: Lidiya Mishchenko and Pooya Shoghi explain how to bridge a gap preventing successful patent claims to protect new ...

With the development of deep convolutional neural networks, significant progress has been made in object detection over the past few years. Current detection algorithms demonstrate high accuracy for ...