layer = nn.LeakyReLU(neg_slope, inplace)elifact =='prelu': layer = nn.PReLU(num_parameters=n_prelu, init=neg_slope)elifact =='gelu': layer = nn.GELU()elifact =='hswish': layer = nn.Hardswish(inplace)else:raiseNotImplementedError('activation layer [%s] is not found'% act)returnla...
To address this concern, we introduce EMCAD, a new efficient multi-scale convolutional attention decoder, designed to optimize both performance and computational efficiency. EMCAD leverages a unique multi-scale depth-wise convolution block, significantly enhancing feature maps through multi-scale convolution...
It was employed for our research presented in [1],[2], where a 3D network architecture with two convolutional pathways was presented for the efficient multi-scale processing of multi-modal MRI volumes. If the use of the software positively influences your endeavours, please cite [1]. [1] ...
The system was initially developed for the segmentation of brain lesions in MRI scans. It was employed for our research presented in [1],[2], where a 3D network architecture with two convolutional pathways was presented for the efficient multi-scale processing of multi-modal MRI volumes. If th...
论文笔记——Multi-Scale Dense Convolutional Networks for Efficient Prediction,程序员大本营,技术文章内容聚合第一站。
We also propose a novel framework for solving the 4K video frame interpolation task, based on a multi-scale pyramid network structure. We introduce self-attention to capture long-range dependencies and self-similarities in pixel space, which overcomes the limitations of c...
First, a weight-based feature fusion block is designed to adaptively fuse information from several multi-scale feature maps. The feature fusion block can exploit contextual information for feature maps with large resolutions. Then, a context attention block is applied to reinforce the local region ...
本文提出CornerNet-Lite,是CornerNet两种变形的组合,一个是CornerNet-Saccade,基于attention机制,从而并不需要对图片中的每个像素做详尽的处理。另一个是CornerNet-Squeeze,引入了新的复杂的backbone结构。结合这两个变形可以应用到两个重要情景中:(1)在不降低准确率的情况下挺高效率,同时,在实时检测过程中提高了准确率,...
Multi-scale convolution networks for seismic event classification with windowed self-attention Yongming Huang Yi Xie Guobao Zhang Journal of Seismology(2024) Processing of electrical resistivity tomography data using convolutional neural network in ERT-NET architectures ...
Efficient convolutional network Underwater image enhancement Multi-scale spatial feature modulation Channel mixing modulation 1. Introduction As underwater work continues to develop rapidly, the longstanding and challenging task of underwater image enhancement has attracted much attention. The goal of underwa...