Tech Xplore on MSN

AI model predicts robberies across US cities with 86.3% accuracy

Researchers have developed an artificial intelligence model that predicts crime more accurately than several existing ...
IEEE

Adversarial Autoencoder Data Synthesis for Enhancing Machine Learning-Based Phishing Detection Algorithms

Abstract: Supervised machine learning is often used to detect phishing websites. However, the scarcity of phishing data for training purposes limits the classifier's performance. Further, machine ...
GitHub

Geometric Adversarial Attacks and Defenses on 3D Point Clouds

This code repository is based on our arXiv tech report. Please read it for more information. Deep neural networks are prone to adversarial examples that maliciously alter the network's outcome. Due to ...
IEEE

Adversarial Autoencoder Network for Hyperspectral Unmixing

Abstract: Spectral unmixing (SU), which refers to extracting basic features (i.e., endmembers) at the subpixel level and calculating the corresponding proportion (i.e., abundances), has become a major ...
Beebom

What Is Generative AI and Why Is It Important?

Generative AI is an Artificial Intelligence system that can generate new content such as text, code, images, music, videos, audio, and more. Nearly all Generative AI models are transformer-based. From ...
C&EN

Interpolation of Imaging Mass Spectrometry Data by a Window-Based Adversarial Autoencoder Method

Department of Cellular and Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka 431-3192, Japan Department of Cellular and Molecular Anatomy, Hamamatsu University School of ...
GitHub

Evading Provenance-Based ML Detectors with Adversarial System Actions

gadget-finder Folder containing the code and data to execute the gadget-finder algorithms. intrusion-detection-system Folder containing the code and data files for IDS execution. Driver script for ...
Frontiers

Subject-invariant feature learning for mTBI identification using LSTM-based variational autoencoder with adversarial regularization

Developing models for identifying mild traumatic brain injury (mTBI) has often been challenging due to large variations in data from subjects, resulting in difficulties for the mTBI-identification ...