Attention Mechanism has become very popular in the field of mechanical fault diagnosis in
recent years and has become an important technique for scholars to study and apply. The …

We present SegFormer, a simple, efficient yet powerful semantic segmentation framework
which unifies Transformers with lightweight multilayer perceptron (MLP) decoders …

Dynamic neural network is an emerging research topic in deep learning. Compared to static
models which have fixed computational graphs and parameters at the inference stage …

Recently, it has been demonstrated that the performance of a deep convolutional neural
network can be effectively improved by embedding an attention module into it. In this work, a …

Pixel-wise regression is probably the most common problem in fine-grained computer vision
tasks, such as estimating keypoint heatmaps and segmentation masks. These regression …

Neural networks have dominated the research of hyperspectral image classification,
attributing to the feature learning capacity of convolution operations. However, the fixed …

Image segmentation is the task of associating pixels in an image with their respective object
class labels. It has a wide range of applications in many industries including healthcare …

Various deep learning methods have been proposed to segment breast lesions from
ultrasound images. However, similar intensity distributions, variable tumor morphologies …

Rice leaf diseases are a major cause of declining rice production and quality. The early
identification and control of rice leaf diseases is critical for maintaining rice quality and …

注意力机制因其优秀的效果与即插即用的便利性, 在深度学习任务中得到了越来越广泛的应用.
主要着眼于卷积神经网络, 对卷积网络注意力机制发展过程中的各种主流方法进行介绍 …