Moreover, we design the cross-scale feature fusion module which contains three path to effectively fuse semantic features with different resolutions while enhancing multi-scale feature representation via cross-edge connections from inputs to last path. Experiments on Cityscapes demonstrate that CFFNet ...
Although traditional multi-scale detection networks have been successful in solving problems with such large variations, they still have certain limitations: (1) The traditional multi-scale detection methods note the scale of features but ignore the correlation between feature levels. Each feature map ...
Feature Enhancement auxiliary network is designed to provide the shallow features to the deep features,and the cross-scale interactive feature enhancement module(CIFEM)is used to enhance the attention ability of the fine-grained features.Thirdly,the Cross-scale Interactive Feature fusion FPN network(...
proposed (MPCFusion). To exploit deeper texture details, a feature extraction module based on convolution and vision Transformer is designed. With a view to correlating the shallow features between different modalities, a parallel cross-attention module is proposed, in which a parallel-channel model ...
A cross-regional attention module that fuses multi-scale features based on graph convolution with multi-head attention. It is able to make local features conditioned by shared global features, quantify their relationships in feature space, and fuse them with each other according to such relationships...
FCSU-Net: A novel full-scale Cross-dimension Self-attention U-Net with collaborative fusion of multi-scale feature for medical image segmentation ? 2024 Elsevier LtdRecently, ViT and CNNs based on encoder鈥揹ecoder architecture have become the dominant model in the field of medical image segmentat...
摘要: Developed a new generalized medical image segmentation network, FCSU-Net.Proposed a collaborative approach of feature fusion.Complete self-attention from multiple perspectives based on global information.关键词: KeywordsMedical image segmentationUNetSelf-attentionFeature fusion ...
The recently developed vision transformer (ViT) has achieved promising results on image classification compared to convolutional neural networks. Inspired by this, in this paper, we study how to learn multi-scale feature representations in transformer models for image classification. To this end, we ...
Design a Multimodal Transformer Mixer to fuse RGB-T complementary information.Develop a two-stream cross-modal collaborative feature representation method... W Kong,J Liu,Y Hong,... - 《Expert Systems with Applications》 被引量: 0发表: 2024年 CMPNet: A cross-modal multi-scale perception networ...
The adaptive cross-scale ROI fusion (ACSF_ROI) module adaptively selects important anchors for large-scale feature extraction and performs cross-scale fusion with the features of all anchors. Relying on this feature extraction method, the detection model can learn features in different fields of ...