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

Radar-Based Vital Signal Extraction via Morphological Component Analysis

Abstract: Noncontact monitoring of cardiopulmonary activity using radar has been a long-standing challenge, especially in dynamic environments where motion artifacts and environmental clutter ...
IEEE

A Cardiac-Gating Method for Human Cerebral Hemodynamic Signal Extraction

Abstract: Cerebral hemodynamic monitoring is crucial for diagnosing neurovascular conditions, but existing imaging modalities that have been used on the clinical side have the limitations of bulky ...
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 ...
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 ...
Ars Technica

Anthropic launches Cowork, a Claude Code-like for general computing

Anthropic’s agentic tool Claude Code has been an enormous hit with some software developers and hobbyists, and now the company is bringing that modality to more general office work with a new feature ...
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 ...
IEEE

A Dynamic Feature Caching Mechanism for Accelerating CNN Real-time Inference

Abstract: To address the computational efficiency bottle-neck faced by large-scale convolutional neural networks when deployed on edge devices, this paper proposes a dynamic feature caching mechanism ...
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 ...