论文:Text-Attentional Convolutional Neural Network for Scene Text Detection 阅读笔记,程序员大本营,技术文章内容聚合第一站。
Lung adenocarcinoma identification based on hybrid feature selections and attentional convolutional neural networksdoi:10.3934/mbe.2024133Kunpeng LiZepeng WangYu ZhouSihai LiMathematical Biosciences & Engineering
Attentional convolutional neural networks for object tracking [IEEE 2018 Integrated Communications, Navigation, Surveillance Conference (ICNS) - Herndon, VA (2018.4.10-2018.4.12)] 2018 Integrated Communications, Navigation, Surveillance Conference (ICNS) - Attentional convolutional neural networks for ... ...
论文《Dense crowd counting from still images with convolutional neural networks》 创新点:使用深度学习方法估计一张图片中中等、高度拥塞程度的人群; 解决问题: 人群计数算法的一些局限性: (1)当人群规模达到成百上千时,这些算法只... 【论文笔记】Single-Image Crowd Counting via Multi-Column Convolutional Neu...
1. Introduction Convolutional neural networks (CNNs) have seen a sig- nificant improvement of the representation power by going deeper [11], going wider [36, 47], increasing cardinality [45], and refining features dynamically [14], corresponding to advances in many computer vision tasks. Apart...
convolutional neural network (AD-CNN) specially designed for water body extraction from Sentinel-2 imagery. On the one hand, AD-CNN exploits dense connections to allow uncovering deeper features while simultaneously characterizing multiple data complexities. On the other hand, the proposed model also ...
With the great success of deep learning over the last decade, convolutional neural networks (CNNs) have been widely applied to cell detection [8,9], cell segmentation [10–12], cell classification [13,14], etc. Deep learning can automatically learn the optimized features, which are completely...
Our neural network architecture is based on a 3D U-net structure27,28 augmented with multi-head axial self-attention (“axial self-attention” in short)29. The motivation behind self-attention is similar to that of atrous convolution (or dilated convolution) in convolutional neural networks51,52...
[Chen et al., 2017b] Long Chen, Hanwang Zhang, Jun Xiao, Liqiang Nie, Jian Shao, and Tat-Seng Chua. SCA-CNN: spatial and channel-wise attention in convolutional networks for image captioning. In CVPR, 2017. [Cheng et al., 2014] Chen Cheng, Fen Xia, Tong Zhang, Irwin King, and ...
Convolutional neural networks (CNNs) have seen a significant improvement of the representation power by going deeper [12], going wider [38, 49], increasing cardinality [47], and refining features dynamically [16], corresponding to advances in many computer vision tasks. Apart from these strategies...