For specially, we first modify the coordinate attention module and spatial attention module through a multi-branch manner, and then combine them to generate the new Spatial-Coordinate Attention module. In this module, the channel information, location information and spatial information are integrated ...
Besides, in order to generate feature maps with high quality, a novel residual dense block with coordinate attention is proposed. In addition to reducing gradient explosion and gradient disappearance, it can reduce the number of parameters by 5.3 times compared to the original feature pyramid ...
The YOLOv5 loss function consists of three key elements: the target confidence loss, the classification loss, and the coordinate loss. The coordinate loss is computed using CIoU loss, whereas the target confidence loss, classification loss, and loss with logits are computed using BCE with logits ...
This attention block was used for wind downscaling (Liu et al., 2022). • Attention gates (Oktay et al., 2018) that can filter the features propagated through the skip connections has been added to the upsampling step in the AU-Net for precipitation downscaling (Sun and Tang, 2020). ...
It is also known as the receptivity curve. Points on the curve reflect the response to the same signal stimulus, but the result is obtained under several different judgment criteria. The curve is obtained by connecting the points with the False Positive Rate (FPR) as the X coordinate and the...
One of the biggest challenges in future work is to get text output from KuroNet. We need to explore the task of automatically converting these character coordinate lists into a single text sequence for a page in reading order. These text sequences are necessary for machine translation, catalogui...
In this paper, we propose a novel key-point detector with only one-level feature with the stride of 8, which is 75.0% less than methods with the stride of 4. Due to the reduction of the feature layers, firstly we adopt a new key-point labeling method, which can make full use of th...
In the third stage (image reconstruction), we use the CA (Coordinate attention) and SE (Squeeze-and-Excitation) attention mechanism to enable the network to more precisely locate the region of interest by the precise location information obtained, which allows the features extracted in the first ...
In this study, we proposed the CARDU-Net (Coordinate Attention Gate Residual Deformable U-Net) model based on coordinate attention mechanism for the segmentation task, which can extract effective features by accurately locating feature location information and enhance the accuracy of segmentation. The ...
SteganalysisSelection channelCoordinate attentionConvolutional neural networksAccording to the embedding probability used in modern content adaptive steganography, some selection channel aware (SCA) methods have been proposed to enhance the detection performances of existing steganalytic networks. Unlike existing ...