AZoRobotics

Detecting IoT Malware in EV Chargers with Deep Learning

A new study presents a deep learning approach for IoT malware detection in EV charging stations, addressing key limitations ...
European Medical Journal

AI Model Boosts Lung Cancer Detection Accuracy to 96%

A new hybrid AI model improves lung cancer detection on CT scans, achieving over 96% accuracy for early tumour identification ...
Frontiers

Semi-Supervised Learning with Foundation Models for Biomedical Data Analysis: Multimodality, Generative AI, and Clinical Adaptation

Biomedical data analysis has evolved rapidly from convolutional neural network-based systems toward transformer architectures and large-scale foundation ...
Medical Dialogues

AI Tool Shows High Accuracy in TB Drug-Resistance Screening, ICMR-NIRT Study Finds

India: A recent study reports that an artificial intelligence (AI) system demonstrated 92-100% accuracy in interpreting ...
T&D

JSHP Showcases Network Transformers with Real-World Testing

Visit JSHP at IEEE PES T&D Conference and Exhibition Booth 4005 to see a real network transformer unit designed and manufactured in accordance with ANSI/IEEE C57.12.40 and CSA standards. Unlike static ...
IEEE

Deep Convolutional Transformer Network with Optional CFO Compensation: A Framework for Automatic Modulation Recognition

Abstract: Automatic modulation recognition (AMR) methods in wireless communication systems can identify the modulation type of received signals without relying on any prior information. However, the ...
imdb.com

Cartoon Network's Transformers Animated Gets Nearly 20-Year-Old Original Art Reveal

IMDb.com, Inc. takes no responsibility for the content or accuracy of the above news articles, Tweets, or blog posts. This content is published for the entertainment of our users only. The news ...
IEEE

BiConformer: EEG-Based Cognitive Load Assessment Using a Bidirectional Convolutional Transformer Network

Abstract: Cognitive load assessment through electroencephalography (EEG) signals represents a crucial research frontier in brain–computer interface (BCI) development. To systematically investigate the ...
Frontiers

Robust automated preclinical fMRI preprocessing via a multi-stage dilated convolutional Swin Transformer affine registration

Accurate preprocessing of functional magnetic resonance imaging (fMRI) data is crucial for effective analysis in preclinical studies. Key steps such as denoising, skull-stripping, and affine ...