- An efficient dual feature fusion model of feature extraction for ...🔍
- Multi|scale fusion and efficient feature extraction for enhanced sonar ...🔍
- Efficient Feature Extraction and Late Fusion Strategy for Audiovisual ...🔍
- YOLOv3|DPFIN🔍
- A multi|level feature fusion method with deep neural network for ...🔍
- A Dual|Model Architecture with Grouping|Attention|Fusion ...🔍
- An efficient fusion algorithm combining feature extraction and ...🔍
- A dual|track feature fusion model utilizing Group Shuffle Residual ...🔍
An efficient dual feature fusion model of feature extraction for ...
An efficient dual feature fusion model of feature extraction for ...
This article presents an efficient FE framework, ie, a dual feature fusion model (DFFM), to address these issues.
An efficient dual feature fusion model of feature extraction for ...
Conventional feature extraction (FE) and spatial or context-preserving filters have been extensively studied when applying hyperspectral images (HSIs).
(PDF) An efficient dual feature fusion model of feature extraction for ...
PDF | On Jul 21, 2023, Xianyue Wang and others published An efficient dual feature fusion model of feature extraction for hyperspectral ...
Multi-scale fusion and efficient feature extraction for enhanced sonar ...
To verify the effectiveness of the proposed method, we conduct a series of experiments on the SCDN dataset and made comparative analyses with current leading ...
Efficient Feature Extraction and Late Fusion Strategy for Audiovisual ...
To tackle this challenge, we extracted rich dual-channel visual features based on ResNet18 and AUs for the video modality and effective ...
YOLOv3-DPFIN: A Dual-Path Feature Fusion Neural Network for ...
The proposed model conducts efficient feature extraction via the Dual-Path Network (DPN) module and the fusion transition module, and adopts ...
A multi-level feature fusion method with deep neural network for ...
A model for achieving high-quality rendering using single image features. ... Transformer and CNN based approach to enhance training robustness and feature ...
A Dual-Model Architecture with Grouping-Attention-Fusion ... - MDPI
Specifically, the model employs two different convolutional neural networks (CNNs) for feature extraction, where the grouping-attention-fusion strategy is used ...
An efficient fusion algorithm combining feature extraction and ...
Then, the initial fused image is optimized by a variational model which contains a fidelity term and a regularization term. The fidelity term is to retain the ...
A dual-track feature fusion model utilizing Group Shuffle Residual ...
introduced a novel method, the Cascade Wavelet Attention Network (CWAN), for accurately identifying grape leaf diseases. CWAN combines a Cascade ...
Gating Mechanism Based Feature Fusion Networks for Time Series ...
Based on the dual consideration of temporal correlation features and pattern features, we designed a time series classification method based on two-channel ...
MDTrans: Multi‐scale and dual‐branch feature fusion network ...
Additionally, Dual Branch Information Fusion Block is designed to fuse local and global features from the two branches. Furthermore, Multi- ...
Dynamic Feature Enhancement for Multimodal Image Fusion with ...
However, fusion models based on convolutional neural networks encounter limitations in capturing global image features due to their focus on ...
DDCNN-F: double decker convolutional neural network 'F' feature ...
1. A novel Double Decker Convolution Neural Network (DDCNN) feature fusion automated framework is designed for skin lesion classification of ...
A Multi-Branch Feature Fusion Strategy Based on an Attention ...
Convolution neural networks (CNNs) can extract rich feature details from images and are used by most researchers [4,5,6]. However, increasingly, researchers are ...
[PDF] ICAFusion: Iterative Cross-Attention Guided Feature Fusion for ...
reducing model complexity and computation cost. Effective feature fusion of multispectral images plays a crucial role in multi-spectral object detection ...
Deep feature fusion classification network (DFFCNet) - NCBI
Therefore, we fuse the features extracted by EfficientNetV2 and ResNet. Deep learning has a strong advantage in feature extraction, while SVM ...
Spatiotemporal Feature Fusion for Video Summarization
This spatiotemporal-based VS method effectively selects the most representative frames from the extracted spatiotemporal features. Unlike traditional methods, ...
A Video Action Recognition Method via Dual-Stream Feature Fusion ...
Third, this designs a multi-scale attention mechanism (MSAM) to enhance the feature extraction stage and obtain higher quality classification features. The ...
Ancient mural segmentation based on multiscale feature fusion and ...
A dual attention-enhanced feature fusion module is proposed for multiscale decoder feature fusion to improve the mural segmentation effect. This ...