IEEE

Adversial Learning Through GAN and Feature Extraction Through CNN for Deep Fake Detection

Abstract: Deepfake technology, using deep learning, creates highly realistic yet artificial media, creating challenges for security and privacy. Convolutional Neural Networks (CNNs) play a crucial ...
IEEE

Feature Extraction and Classification of ECG Signals Using 2-D CNN

Abstract: This work investigates ECG arrhythmia classification using two-dimensional convolutional neural networks (2D CNNs) applied to wavelet-based time–frequency representations. Three CNN ...
IEEE

A Hybrid Approach Using CNN Feature Extraction and SVM/XGBoost for Lung Nodule Classification

Abstract: Early detection of lung cancer is highly beneficial for patient survival. This paper proposes a hybrid deep learning diagnostic pipeline for pulmonary nodules in chest CT. We constructed a ...
IEEE

Feature Extraction Based On Signal Similarity for Damage Detection with Ultrasonic Guided Waves

Abstract: Structural health monitoring is crucial for safeguarding critical infrastructure and requires the use of traceable methods. Hence, using explainable machine learning (ML) becomes ...
CNBC

AI startup Replit launches feature to vibe code mobile apps

Replit's new feature allows users to create publishable and monetizable mobile apps using only natural language prompts. As more vibe-coding products come online, some software companies could see one ...
IEEE

Guardian Veil: Fortifying IoT Locking Systems with CNN Embedded QR Codes and Signal Sorcery

Abstract: With the rise of IoT-driven locking mechanisms, integrating advanced technologies like steganography, QR codes, and embedded systems presents a promising avenue for strengthening ...
IEEE

Mask R-CNN-based bushing segmentation with refined feature extraction and precise localization

Abstract: Accurate localization and segmentation of power equipment are critical for automated inspection systems, particularly in detecting structural and thermal anomalies. However, the task remains ...
IEEE

A Hybrid Feature Extraction and Classification Framework for Depression Detection using Deep Learning and Machine Learning Techniques

Abstract: Depression is most common mental disorder that is affecting approximately 280 million individuals in the world. The stigma and lack of acceptance and awareness is still influencing people ...
IEEE

Human Age Group Classification Using CNN and Vision Transformer-Based Feature Extraction

Abstract: The human face reveals significant information about an individual’s identity, age, gender, emotion, and ethnicity. In face-to-face communication, age plays a vital role, influencing ...
IEEE

Determination of the most significant features for hyperglycemia detection and their extraction from electrocardiogram signal

Abstract: Hyperglycemia, characterized by elevated blood glucose levels, is prevalent among diabetic patients and poses risks of severe complications if left unmanaged. This study investigates the ...
The Raw Story

Trump stuns with wild answer to CNN reporter: 'This man has the nuclear codes!'

Nicole Charky-Chami is a senior editor based in Los Angeles, writing and producing breaking news. She teaches journalism courses for UCLA Extension and previously taught at Loyola Marymount University ...
Wired

AI Models Are Starting to Learn by Asking Themselves Questions

An AI model that learns without human input—by posing interesting queries for itself—might point the way to superintelligence. Save this story Save this story Even the smartest artificial intelligence ...