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 ...
IEEE

Investigating SAR Data Denoising: A Comparative Analysis of CNN Models with Multi-Channel Signal Processing Features

Abstract: This paper investigates the necessity for denoising in Synthetic Aperture Radar (SAR) dataset, emphasizing the comparison of three distinct neural networks: U-Net, ResNet, and DeepDeblur.
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

1D-DCNN: 1D Dilated CNN for Efficient Depression Diagnosis Based on Audio Signal

Abstract: Depression is a prevalent mental disorder that involves prolonged feelings of sadness or loss of interest in activities for a long time, even self-harm and suicidal. However, due to low ...
IEEE

A Novel De-Mirroring Approach for Capacitance and Resistance Extraction in Complementary FET: A Quasi-Static Small Signal Model

Abstract: A quasi-static small signal model is vitally important to bridge the gap in device circuit co-design. To the best of our knowledge, for the first time in this paper, we proposed the ...
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

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 ...
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 ...