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 ...
IEEE

SCFNet:A Swin-CNN Synergistic Fusion Network For Urban and Rural Water Extraction In Remote Sensing Images

Accurate monitoring of water resources is essential for disaster risk reduction and sustainable development amid global climate change. At present, various methods based on convolutional neural ...

How AI coding agents work—and what to remember if you use them

At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...
IEEE

FCTFANet: A Fused CNN-Transformer Feature Aggregator Network for Image Restoration

Abstract: Convolutional neural networks (CNNs) have been foundational in deep learning architectures for image processing, and recently, Transformer networks have emerged, bringing further ...
IEEE

A Hybrid Framework for Acute Lymphoblastic Leukemia Identification Utilizing VIT-CNN Fusion and Immunologically Inspired Deep Feature Selection

Abstract: Acute Lymphoblastic Leukemia (ALL) is a serious blood cancer characterized by the abnormal growth of progenitor white blood cells, which interferes with normal blood cell production. Early ...
IEEE

MST-ResFLNet: Multi-Scale Temporal-Spectral Feature Fusion for Heart Sound Signal Analysis

Abstract: Cardiac auscultation is a key non-invasive heart disease diagnostic method, but traditional heart sound diagnosis depends highly on physicians' experience, with subjective bias. Deep ...
IEEE

A Dual-Branch Global-Local Feature Learning Network by Integrating CNN and Transformer for Remote Sensing Image Super-Resolution

Abstract: In the task of remote sensing image super-resolution reconstruction, both CNN and Transformer have demonstrated remarkable performance. However, many existing two-branch models only fuse the ...
IEEE

CNN-LSTM for Dynamic Gesture Recognition in Hand Electrostatic Signal Processing

Abstract: As a ubiquitous interaction modality in daily life, hand gestures convey rich interactive information. Particularly under the evolving paradigm of Natural User Interface (NUI), gesture ...
Frontiers

Multiscale CNN-state space model with feature fusion for crop disease detection from UAV imagery

Accurate detection of crop diseases from unmanned aerial vehicle (UAV) imagery is critical for precision agriculture. This task remains challenging due to the complex backgrounds, variable scales of ...
IEEE

Data Analytics for Automated Feature Extraction and Anomaly Detection in a Class of Industrial Manufacturing Processes

Abstract: Industry 4.0/Smart Manufacturing is transforming the manufacturing industry through the integration of technologies such as the Internet of Things (IoT), big data, and cloud computing. These ...
IEEE

Explainability of CNN Based Classification Models for Acoustic Signal

Abstract: Explainable Artificial Intelligence (XAI) has emerged as a critical tool for interpreting the predictions of complex deep learning models. While XAI has been increasingly applied in various ...
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 ...