We propose an attention-based multiscale transformer network (AMTNet) that utilizes a CNN-transformer structure to address this issue. Our Siamese network based on the CNN-transformer architecture uses ConvNets as the backbone to extract multiscale features from the raw input image pair. We then ...
Single-image dehazing networkMulti-scale feature fusionEd-local binary patternSOS feature enhancementSE attention mechanismNETWORKSIt is very challenging to ... X Zhang,J Li,Z Hua - 《Signal Processing Image Communication A Publication of the the European Association for Signal Processing》 被引量: ...
Recurrently exploring class-wise attention in a hybrid convolutional and bidirectional LSTM network for multi-label aerial image classification. Aerial image classification is of great significance in the remote sensing community, and many researches have been conducted over the past few years. Amon......
To this end, we introduce a multiscale deformable transformer network to leverage echo contexts from image patches of varying spatial scales. Meanwhile, a multihead deformable self-attention mechanism is introduced for capturing precipitation spatiotemporal dynamics in a global manner. Moreover, to ...
Particular attention is turned to the investigation of criteria for crack initiation and crack growth. A drawback of the macroscopic simulation is that the real physical phenomena leading to the nonlinear behavior are only modeled phenomenologically. For concrete, the nonlinear behavior is characterized ...
Although some researchers have attempted to address this issue, we exploit ideas surrounding the field and proposed a more prominent architecture called dense attention feature pyramid network (DAF-Net) for multiscale object detection. DAF-Net consists of two attention models, the spatial attention ...
A new supervised multi-head self-attention autoencoder for health indicator construction and similarity-based machinery RUL prediction Remaining useful life (RUL) prediction plays a significant role in the prognostic and health management (PHM) of rotating machineries. A good health indica... Y Qin,...
Most existing image restoration methods focus on defocus blur and motion blur and pay less attention to diffraction degradation, which cannot handle real-world complex degradation well. In this study, to address the challenges in droplet image restoration, we propose a diffraction-Gaussian degradation ...
Second, our model incorporates the fuzzy-deep neural network learning module, infused with fuzzy logic principles to enhance adaptability to the inherent vagueness in sentiment expressions. Furthermore, we integrate the dual attention mechanism that dynamically focuses on pivotal aspects within multimodal ...
On the other hand, convolutional neural network (CNN) can automatically extract useful features from the input data (Fang et al., 2020, Zhao and Du, 2016), which are favorable to analyze the landslide susceptibility. Given the fact, CNN that is thought capable of such “black box” ...