IEEE

A Novel Parallel Convolution-Self-Attention Neural Network Based Calibration Scheme for Pipelined and Pipelined-SAR ADCs

Abstract: This paper presents a novel parallel convolution-self-attention neural network (PCSANN) based calibration scheme for Pipelined and Pipelined-SAR ADCs. Combining convolution neural network ...
IEEE

Integrated Smart Parking System Using Internet of Things (IoT) and Digital Image Processing with Faster Region Based Convolutional Neural Network (Faster R-CNN) and Optical ...

Abstract: Parking is an integral part of driving, especially in urban areas. However, inefficient parking systems often cause drivers to spend a significant amount of time just to find a parking spot, ...
IEEE

Enhanced Convolution Neural Network with Optimized Pooling and Hyperparameter Tuning for Network Intrusion Detection

Abstract: Network Intrusion Detection Systems (NIDS) are essential for protecting computer networks from malicious activities, including Denial of Service (DoS), Probing, User-to-Root (U2R), and ...
IEEE

Multiscale Segmentation-Guided Fusion Network for Hyperspectral Image Classification

Abstract: Convolution Neural Networks (CNNs) have demonstrated strong feature extraction capabilities in Euclidean spaces, achieving remarkable success in hyperspectral image (HSI) classification ...
IEEE

SCADA Data-Driven Spatio-Temporal Graph Convolutional Neural Network for Wind Turbine Fault Diagnosis

Abstract: Supervisory control and data acquisition (SCADA) systems collect vast amounts of multi-sensor monitoring data, which is widely used in the intelligent fault diagnosis of wind turbines with ...
IEEE

Gas Volume Fraction Measurement for Gas-Liquid Two-Phase Flow Based on Dual CNN-Transformer Mixture Neural Network

Abstract: Accurate gas volume fraction (GVF) measurement in gas-liquid two-phase flow remains a key challenge in industrial process monitoring and control. In order to address this, a deep ...
IEEE

Hybrid Approximate Multipliers With Merits Balance for Digital Processing and Neural Networks

Abstract: In this article, hybrid approximate multiplier (HAMs) designs based on the combination of logarithmic multiplication and piecewise linear (PWL) fitting are proposed. After extracting the ...
IEEE

Efficient Group Cosine Convolutional Neural Network for EEG-Based Seizure Identification

Abstract: Epilepsy is a common neurological disease, and its diagnosis usually depends on labor-intensive visual inspection of electroencephalogram (EEG). Although various deep learning-based seizure ...
IEEE

Attention-Based Convolutional Neural Network Model for Skin Cancer Classification

Abstract: Early detection of skin cancer (SC) is paramount for effective treatment. Although convolutional neural networks (CNN) have facilitated automated learning of high-level features from ...
IEEE

DDSC: Shallow Depthwise Separable Convolution Neural Network for Plant Leaf Diseases Classification

Abstract: While most convolution neural network (CNN)-based approaches for plant disease classification improve accuracy through deeper architectures (stacked convolutional and pooling layers), this ...
IEEE

Multiattention Spatiotemporal Fusion Graph Neural Network for Chemical Process Fault Diagnosis

Abstract: Fault diagnosis of complex industrial processes becomes challenging due to temporal and spatial dependencies in process data. This means that the emergence and evolution of faults are ...