1) Hard Attention (Image Cropping) 2) Soft Attention (Highlight attentional area keeping the image size same) What are AutoEncoders? and what are transformers? Autoencoders take input data, compress it into a code, then try to recreate the input data from that summarized code. It’s ...
Inter- and intra-uncertainty based feature aggregation model for semi-supervised histopathology image segmentation 2024, Expert Systems with Applications Citation Excerpt : However, the training process can be laborious and prone to instability. ( 4) Contrastive learning (CL) (Basak & Yin, 2023; Chai...
1.4理想局部特征的性质局部特征通常具有空间范围,即上述像素的局部邻域。与经典分割相比,这可以是图像的任何子集。区域边界不必对应于图像外观的变化,例如颜色或纹理。而且,多个区域可能重叠,并且图像的“不感兴趣”部分(例如均匀区域)可以保持未被覆盖。 理想情况下,人们希望这些局部特征对应于语义上有意义的对象部分。然...
underwater stereo matching; Deep Inverse Patchmatch Network; multilevel recurrent neural network; Attentional Feature Fusion; real-world underwater scenarios1. Introduction Stereo matching aims at recovering a scene’s geometric information via stereo disparity estimation, which is a long-standing vision-...
Attentional local contrast networks for infrared small target detection. IEEE Trans. Geosci. Remote Sens. 2021, 59, 9813–9824. [Google Scholar] [CrossRef] Zhu, R.; Zhuang, L. Unsupervised Infrared Small-Object-Detection Approach of Spatial–Temporal Patch Tensor and Object Selection. Remote ...