1、对输入的图像信息做更细致的编码 Position focused attention network for image-text matching(IJCAI 2019) 模型介绍:PFAN采用position focused attention机制来强调图像中的物体位置关系,更好地编码图像。 Learning Visual Relation Priors for Image-Text Matching and Image Captioning with Neural Scene Graph Generat...
VLMo论文的模型核心是一个transformer encoder的结构,提出了MoME transformer(mixture-of-modality-expert)。 一个标准的transformer block里先有一个Layer Norm,接下来是一个MSA(multi-head self-attention),然后是Layer Norm,然后是一个FFN(feed-forward network),最后有一个residual。 本文的transformer block结构:本...
Attention mechanisms are widely used in current encoder/decoder frameworks of image captioning, where a weighted average on encoded vectors is generated at each time step to guide the caption decoding process. However, the decoder has little idea of whether or how well the attended vector and the...
andretinitis pigmentosaare all examples of common retinal conditions[2]. Ophthalmologists need a high degree of attention and precision for an accurate diagnosis. A slight mistake during diagnosis may affect/corrupt the patient’s sight and even cause blindness. Under massive workload,Diabetic Retinopat...
Self-Image Profile in Children and Adolescents with Attention Deficit/ Hyperactivity Disorder and the Quality of Life in Their Parents We explored the impact of clinical response to treatment for Attention Deficit/Hyperactivity Disorder (ADHD) in children and adolescents on the subsequent ... V Gorm...
This gap underscores the need for a novel approach that can harness the strengths of both DB and RL, along with advanced attention mechanisms, to set a new benchmark in image denoising. Dense blocks CNNs consist of three components: input layer, hidden layer, and output layer. The main ...
Although there have been some previous surveys on SISR [31,32,33,34,35,36], our survey differs from them in that we focus on the performance and progress of SISR techniques that address their top challenges. Unlike earlier works that mostly investigated traditional SISR algorithms or focused ...
[111] Yulun Zhang, Kai Li, Kunpeng Li, Yun Fu. MR Image Super-Resolution With Squeeze and Excitation Reasoning Attention Network. CVPR, 2021.[Paper] [112] Aupendu Kar, Prabir Kumar Biswas. Fast Bayesian Uncertainty Estimation and Reduction of Batch Normalized Single Image Super-Resolution Netwo...
In view of the defects of the current fusion method in the detail information retention effect of the original image, a fusion architecture based on two stages is designed. In the training phase, combined with the polarized self-attention module and the DenseNet network structure, an encoder-...
The first stage introduced atrous convolution with autocorrelation matching based on spatial attention to improve similarity detection. In the second stage, the superglue method was proposed to eliminate false warning regions and repair incomplete regions, thus improving the detection accuracy of the ...