为了解决上述问题,我们设计了一种多尺度扩张残差块(MDRB)fMDRB multi-scale dilated residual block (MDRB),它不仅可以有效地扩大感受野 receptive field 以感知帧之间的大像素运动, 还可以 在扩张卷积的帮助下可以很好地保留对象边界细节 捕获多尺度上下文信息。 具体的是: 首先堆叠两个 3 × 3 和 5 × 5 卷...
Hybrid dilation convolution and double dilation convolution were used in the codec stage to enhance the receptive field. Zhang et al.15 proposed the scale attention mechanism to effectively address the multiscale problem of liver and tumor segmentation. Kushnure et al.16 developed HFRU-Net to ...
This paper addresses multi-sensor data fusion with incremental learning ability. A new cost function is proposed for the receptive field weighted regressio... J Su,J Wang,Y Xi - 《IEEE Transactions on Systems Man & Cybernetics Part B Cybernetics A Publication of the IEEE Systems Man & Cyberne...
Although FPN-like feature fusion models have achieved remarkable results in the field of computer vision, they still have some shortcomings. On the one hand, as mentioned in the paper33, in the pyramid feature fusion structure, the deep feature information is transferred to the shallow features l...
Li et al. [10] first introduced the dilated convolution for crowd counting, because it is able to achieve a larger receptive field without losing the size of the feature map by inserting zeros into the convolution kernel. However, we believe that only a large receptive field is not enough ...
A network that utilizes expansive receptive fields and local information learning was proposed for the accurate segmentation of breast fibroadenomas in sonography. The architecture comprises the Hierarchical Attentive Fusion module, which conducts local information learning through channel-wise and pixel-wise...
In this paper, we aim to improve the performance of single-image super-resolution (SISR) by designing a more effective feature extraction module and a better fusion scheme for integrating hierarchical features. Firstly, we propose a selective multi-scale module (SMsM) to adaptively aggregate multi...
Furthermore, we introduce a multi-scale feature fusion strategy that amalgamates contextual information and expands the receptive field to enhance the network's performance in handling challenging scenarios, such as textureless and occluded regions. 展开 ...
We replaced the Fusion module with different Fusion methods. Other modules remain unchanged, and the experimental results are shown in Table 3 benefit by the multiple pyramid module designed by us, the receptive field is not only increased in a single dimension, but also the feature information ...
to mitigate the detrimental effects that noise has on the performance of residual block models. By expanding the receptive field and adding the CBAM attention module, as illustrated in Fig.5, the CRA block overcomes the limitations of receptive fields and information loss during feature extraction,...