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Sarcopenia prediction using shear-wave elastography, grayscale ultrasonography, and clinical information with machine learning fusion techniques: feature-level fusion vs. score-level fusion
This study aimed to develop and evaluate a sarcopenia prediction model by fusing numerical features from shear-wave elastography (SWE) and gray-scale...
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Speech emotion classification using feature-level and classifier-level fusion
AbstractEmotion plays a vital role in every living being. Understanding emotion is a very complex task for everyone, but if possible, it will work...
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Defocus blur detection via adaptive cross-level feature fusion and refinement
Convolutional neural networks have achieved competitive performance in defocus blur detection (DBD). However, due to the different receptive fields...
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MLANet: multi-level attention network with multi-scale feature fusion for crowd counting
Estimating the population in a given scene is a process known as crowd counting. The field has recently garnered significant attention, and many...
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Efficient fused convolution neural network (EFCNN) for feature level fusion of medical images
This paper proposes an Efficient Fused Convolution Neural Network (EFCNN) for feature-level fusion of medical images. The proposed network...
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Combined CNN LSTM with attention for speech emotion recognition based on feature-level fusion
According to the problem that emotional features cannot be well represented by a single feature and it is difficult to extract in the task of Speech...
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Patchlpr: a multi-level feature fusion transformer network for LiDAR-based place recognition
LiDAR-based place recognition plays a crucial role in autonomous vehicles, enabling the identification of locations in GPS-invalid environments that...
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Enhancing microblog sentiment analysis through multi-level feature interaction fusion with social relationship guidance
In sentiment analysis of microblogs that involve social relationships, a common approach is to expand the features of target microblogs using...
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STFormer: Cross-Level Feature Fusion in Object Detection
Object detection algorithms can benefit from multi-level features, which encompass both high-level semantic information and low-level location...
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Infrared and visible image fusion based on quaternion wavelets transform and feature-level Copula model
To solve the problems that the correlation of multi-scale coefficients is ignored, as well as inaccurate identification of complementarity and...
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Semantic segmentation-assisted instance feature fusion for multi-level 3D part instance segmentation
Recognizing 3D part instances from a 3D point cloud is crucial for 3D structure and scene understanding. Several learning-based approaches use...
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YOLOF-F: you only look one-level feature fusion for traffic sign detection
This paper proposes a detector that focuses on multi-scale detection problems and effectively enhances the detection performance to solve the problem...
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CoCoNet: Coupled Contrastive Learning Network with Multi-level Feature Ensemble for Multi-modality Image Fusion
Infrared and visible image fusion targets to provide an informative image by combining complementary information from different sensors. Existing...
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MFCINet: multi-level feature and context information fusion network for RGB-D salient object detection
Recently, RGB-D salient object detection (SOD) has aroused widespread research interest. Existing methods tend to treat equally features at different...
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A dual-structure attention-based multi-level feature fusion network for automatic surface defect detection
The detection of surface defects is crucial to industrial manufacturing. In recent years, numerous detection methods based on computer vision have...
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Multimodal Face and Ear Recognition Using Feature Level and Score Level Fusion Approach
Recent years have seen a significant increase in attention in multimodal biometric systems for personal identification especially in unconstrained...
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Text-Independent Speaker Recognition System Using Feature-Level Fusion for Audio Databases of Various Sizes
To improve the speaker recognition rate, we propose a speaker recognition model based on the fusion of different kinds of speech features. A new type...
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A multi-level feature weight fusion model for salient object detection
Although the Fully Convolutional Neural Networks (FCNs) has achieved good performance in salient object detection, there are problems, such as...
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Multi-level receptive field feature reuse for multi-focus image fusion
Multi-focus image fusion, which is the fusion of two or more images focused on different targets into one clear image, is a worthwhile problem in...
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High-to-low-level feature matching and complementary information fusion for reference-based image super-resolution
The aim of the reference-based image super-resolution (RefSR) is to reconstruct high-resolution (HR) when a reference (Ref) image with similar...
