Abstract: Video-based anomaly detection plays a crucial role in applications like surveillance, healthcare, and autonomous systems. Deep learning techniques, such as Convolutional Neural Networks ...

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 ...

ABSTRACT: The accelerating sophistication of cyberattacks poses unprecedented challenges for national security, critical infrastructures, and global digital resilience. Traditional signature-based ...

ABSTRACT: The accelerating sophistication of cyberattacks poses unprecedented challenges for national security, critical infrastructures, and global digital resilience. Traditional signature-based ...

Deep learning has emerged as a transformative tool for the automated detection and classification of seizure events from intracranial EEG (iEEG) recordings. In this review, we synthesize recent ...

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

1 Department of Computer Science, College of Computing and Information Technology, Shaqra University, Shaqra, Saudi Arabia 2 InnoV'COM Laboratory-Sup'Com, University of Carthage, Ariana, Tunisia ...

Abstract: The rapid expansion of data from diverse sources has made anomaly detection (AD) increasingly essential for identifying unexpected observations that may signal system failures, security ...

You’ve probably seen it all over your feeds: Fitness pros and physical therapists talking about “training the deep core.” But unlike crunches or Russian twists, these exercises don’t come with a pump ...

The rapid advancement of artificial intelligence (AI) in medical image analysis, particularly deep learning (DL) algorithms, has provided novel solutions for automated TN detection. However, existing ...