A dual attention-enhanced feature fusion module is proposed for multiscale decoder feature fusion to improve the mural segmentation effect. This module uses a cross-level aggregation strategy and an attention mechanism to weight the importance of different feature levels to obtain multilevel semantic ...
Multiscale feature fusion (MSFF) module Compared with the existing methods, we add a MSFF module to fuse the output of all the layers in the block after the last layer. Let xl be the output of the last layer in the block: $$x_{l} = H(x_{l - 1} ) \otimes H(x_{l - 2...
摘要: BEG-YOLO's CSP-GFPN and BEA enhance small defect detection.CSP-GFPN in BEG-YOLO boosts feature fusion for defect detection.BEA in BEG-YOLO filters features, focusing on key regions.BEG-YOLO surpasses other YOLO models in detection metrics.关键词:...
Third, we design a cross-regional attention module based on graph attention network. It quantifies underlying relationships among all the local features under certain conditions interpreted by global features. Based on such relationships, each conditional local feature vector is able to search across ...
In this paper, we propose a multiscale feature interaction network (MFI-Net) for retinal vessel segmentation, which is a U-shaped convolutional neural network equipped with the pyramid squeeze-and-excitation (PSE) module, coarse-to-fine (C2F) module, deep supervision, and feature fusion. We ...
The ViT feature extractor is initially trained on ImageNet dataset. To enable the model to classify breast cancer images, additional layers have been integrated. Fig. 5 Breakdown of the global stream used in the fusion model. Full size image Following the ViT feature extractor, a batch ...
Thus, a feature pyramid module was added to the model using a multi-scale feature fusion. As such, the low-level features were combined with the high... 孙俊,朱伟栋,罗元秋,... - 《Transactions of the Chinese Society of Agricultural Engineering》 被引量: 0发表: 2021年 基于作物生长模型和...
The proposed feature fusion method can be added to all object detector, such as the one-stage detector, the two-stage detector, anchor-based detector and anchor-free based detector. Experimental results on the COCO 2014 dataset show that the proposed AMF module performs the popular FPN based ...
Fusion-attention mechanism From the first two modules, we obtain the global feature representation \(\:{Z}=[{{z}}_{1},{{z}}_{2},\ldots,{{z}}_{{n}}]\) embedded with dependency relations and the multi-level local feature representation \(\:{F}=[{{f}}_{1},{{f}}_{2},\l...
In addition, the input feature map elements are enhanced or suppressed by the attention module in order to extract salient features more accurately. The proposed method was validated on two commonly used expression data sets CK+ and RAF-DB, and the recognition rates were 98.77 and 82.83%, ...