CNN Image Classification

Hybrid Attention-Based Residual Network for Image Classification

Abstract: Residual Attention Networks (RANs) are a class of Convolutional Neural Networks (CNNs) that integrate attention mechanisms into deep architectures. RANs employ stacked attention modules to ...

IEEE

An SAGPSO-CNN Approach for Supervised Fault Classification in MVdc Shipboard Power Systems

Abstract: All-electric ships (AESs) utilizing medium-voltage dc (MVdc) shipboard power systems (SPSs) rely on a limited number of generators to supply power to propulsion units and onboard loads. To ...

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 ...

WiMi Releases Next-Generation Hybrid Quantum Neural Network Structure Technology, Breaking Through the Bottleneck of Image Multi-Classification

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, launched a hybrid quantum neural network structure (H-QNN) ...

IEEE

CWmamba: Leveraging CNN-Mamba Fusion for Enhanced Change Detection in Remote Sensing Images

Abstract: Remote sensing image change detection is crucial for urban construction and environmental monitoring. Recent advancements have seen convolutional neural networks (CNNs) and transformer ...

IEEE

A hybrid CNN-LSTM approach for detecting intracerebral hemorrhage in CT images

Abstract: A Stroke is a life-risk condition caused due to lack in blood flow to the part of the brain. Accurate diagnosis using computed tomographic (CT) scans is crucial for immediate care in the ...

IEEE

Robust Image Steganography Approach Based on Edge Detection Combined With CNN Algorithm

Abstract: Image steganography conceals secret data within a cover image to generate a new image (stego image) in a manner that makes the secret data undetectable. The main problem in image ...

IEEE

Enhanced Image Captioning Using CNN and BLIP Models

Abstract: This research focuses on generating image captions using Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) models. As deep learning advances, the availability of large ...

IEEE

Temporal-Spatial Feature Extraction in IoT-Based SCADA System Security: Hybrid CNN-LSTM and Attention-Based Architectures for Malware Classification and Attack Detection

Abstract: This research presents a Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) model developed for malware classification from IoT devices in the SCADA system and for ...

IEEE

Show inaccessible results

Hybrid Attention-Based Residual Network for Image Classification

An SAGPSO-CNN Approach for Supervised Fault Classification in MVdc Shipboard Power Systems

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

WiMi Releases Next-Generation Hybrid Quantum Neural Network Structure Technology, Breaking Through the Bottleneck of Image Multi-Classification

CWmamba: Leveraging CNN-Mamba Fusion for Enhanced Change Detection in Remote Sensing Images

A hybrid CNN-LSTM approach for detecting intracerebral hemorrhage in CT images

Robust Image Steganography Approach Based on Edge Detection Combined With CNN Algorithm

Enhanced Image Captioning Using CNN and BLIP Models

Temporal-Spatial Feature Extraction in IoT-Based SCADA System Security: Hybrid CNN-LSTM and Attention-Based Architectures for Malware Classification and Attack Detection

RMSO-ConvNeXt: A Lightweight CNN Network for Robust SAR and Optical Image Matching Under Strong Noise Interference

Trump signs order to reclassify marijuana as Schedule III drug

CNN Data Guru Reveals Issue That Could Swing Voters Back to Trump