相关实验视频

Updated: Jun 19, 2026

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
17:06

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

26.1K

通过CSPA-DFN和通过扩散变压器模型的线性交叉注意力来提高LiDAR场景生成中的现实性

Shaoxun Ye1, Xiaoguang Di1, Ming Liao1

  • 1Control and Simulation Center, Harbin Institute of Technology, Harbin 150080, China; National Key Laboratory of Modeling and Simulation for Complex Systems, Harbin 150080, China.

Neural networks : the official journal of the International Neural Network Society
|May 9, 2025
PubMed
概括

这项研究引入了一种新的LiDAR扩散变压器模型,以提高自动驾驶产生的LiDAR场景的视觉质量. 新模型有效地减少了扭曲,并增强了细节,实现了最先进的结果.

关键词:
频道空间平行注意力扩散变压器 扩散变压器激光雷达 (LiDAR) 场景生成线性ReLU交叉注意力交叉注意力

更多相关视频

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

432
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

320

相关概念视频

Linear Approximations01:23

Linear Approximations

For a differentiable function of two variables, linear approximation estimates values near a known point by replacing the curved surface with its tangent plane. Consider the function\begin{equation*}f(x,y)=x^2+3y^2\end{equation*}near the point (2, 1). The exact value at this point is f(2, 1) = 22 + 3(1)2 = 4 + 3 = 7.The linear approximation of f(x, y)) near (a, b) is\begin{equation*}L(x,y)=f(a,b)+f_x(a,b)(x-a)+f_y(a,b)(y-b)\end{equation*}First, compute the partial derivatives: fx(x, y) = 2x and...