10 things I learned from burning myself out with AI coding agents

Like all AI models based on the Transformer architecture, the large language models (LLMs) that underpin today’s coding ...
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

Graph-Based Radiomics Feature Extraction From 2D Retina Images

Abstract: Medical image analysis offers valuable visual support for clinical decision-making, yet the incorporation of quantitative data is essential for deeper diagnostic insight. The radiomics ...
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 ...
The New York Times

Stephen Miller Asserts U.S. Has Right to Take Greenland

In a CNN interview, the Trump aide also echoed the president’s intent to run Venezuela as he laid out a case for the United States to control weaker states by flexing its military might. By Chris ...
IEEE

Intelligent Fault Diagnosis of Motor Bearings Based on Dual-Branch Depthwise Separable CNN With Acoustic–Vibration Signal Fusion

Abstract: The intelligent diagnosis of motor bearings under complex working conditions presents significant challenges, including insufficient feature extraction, limited reliability of ...
IEEE

Research on Communication Signal Recognition based on CNN-LSTM Neural Networks

Abstract: This paper addresses the issue of degraded accuracy in traditional communication signal recognition under low Signal-to-Noise Ratio (SNR) environments by proposing a Convolutional Neural ...
IEEE

SCAFNet: A Semantic Compensated Adaptive Fusion Network for Remote Sensing Images Change Detection

Abstract: Current CNN-Transformer hybrid methods for remote sensing change detection aim to address the limitations of CNNs’ constrained receptive fields and Transformers’ local detail insensitivity.
IEEE

Multilayer Feature Extraction Object Detection Based on Deep Forest

Abstract: With the emergence of various large-scale deep-learning models, in remote sensing images, the object detection effect is also plagued by complex calculations, high costs, and high ...
IEEE

UAGLNet: Uncertainty-Aggregated Global-Local Fusion Network with Cooperative CNN-Transformer for Building Extraction

Abstract: Building extraction from remote sensing images is a challenging task due to the complex structure variations of the buildings. Existing methods employ convolutional or self-attention blocks ...
IEEE

Single-Channel Time-Frequency Overlapping Signal Modulation Recognition Network Based on Multi-Domain Adaptive Feature Fusion

Abstract: With the application of massive wireless devices, the receiver often receives mixed signals with time-frequency overlapping. Automatic modulation classification (AMC) of such mixed signals ...