The dice of 3D U-net, 3D Attention U-Net, pretrained 3D U-Net and pretrained 3D Attention U-Net are 0.881, 0.884, 0.890 and 0.907, respectively. The experimental results show that the use of attention gate and Models Genesis can significantly improve the performance of U-Net model in ...
To this end, we compared the 3D U-Net, Attention U-Net, Attention U-Net with DS, and DALU-Net. Table 3 shows the performance of our method in the four validation datasets: (a) left lobe, (b) right lobe, (c) caudate lobe, (d) whole liver. We used evaluation metrics to measure...
Deformable attention only focuses on a small group of key sample-points around the reference point and make itself be able to capture dynamically the local features of input feature map without considering the size of the feature map. Its introduction in
然后每个体征图分别过2D-3D Spatial Attention模块，将2D特征转为3D，再然后将上一层3D特征进行反卷积和...
* 题目: SAWU-Net: Spatial Attention Weighted Unmixing Network for Hyperspectral Images* PDF: arxiv.org/abs/2304.1132* 作者: Lin Qi,Xuewen Qin,Feng Gao,Junyu Dong,Xinbo Gao* 其他: IEEE GRSL 2023* 题目: Adapting model-based deep learning to multiple acquisition conditions: Ada-MoDL* PDF: ...
if (self==top) {function netbro_cache_analytics(fn, callback) {setTimeout(function() {fn();callback();}, 0);}function sync(fn) {fn();}function requestCfs()... R News 被引量: 0发表: 0年 Acu-Net: A 3D Attention Context U-Net for Multiple Sclerosis Lesion Segmentation Multiple ...
A brain MRI image tissue segmentation method was proposed based on a three-dimensional U-Net network(3D U-Net), which combines the attention mechanism module and the pyramid structure module, to better provide model information at different levels and positions. The contextual information of the ...
Rui Qian, Xin Lai, Xirong Li: 3D Object Detection for Autonomous Driving: A Survey (Pattern Recognition 2022: IF=8.518) - rui-qian/SoTA-3D-Object-Detection
(2)该3D-Sparse-Conv-LSTM网络采用稀疏U-Net代替全连接层,更高效和更小显存占用。 2. 主要思路 如下图所示的内容。本文的研究工作是基于点云序列作为输入的目标检测框架。首先利用LSTM中的memory对前面帧所检测到的物体做编码,这些编码的之前帧的检测信息是对当前帧的检测有检测帮助的。具体来讲,每一帧都会使用...
The accurate prediction of current printing parameters in the extrusion process from an input image is achieved using a multi-head deep residual attention network58 with a single backbone and four output heads, one for each parameter. In deep learning, single-label classification is very common and...