while rust loop for
Dual Attention Network for Scene Segmentation：双线并行的注意力
Dual Attention Network for Scene Segmentation * Authors: [[Jun Fu]], [[Jing Liu]], [[Haijie Tian]], [[Yong Li]], [[Yongjun Bao]], [[Zhiwei Fang]], [[H ......
Bottleneck Transformers for Visual Recognition
Bottleneck Transformers for Visual Recognition * Authors: [[Aravind Srinivas]], [[Tsung-Yi Lin]], [[Niki Parmar]], [[Jonathon Shlens]], [[Pieter Abbee ......
Fully convolutional networks for semantic segmentation
Fully convolutional networks for semantic segmentation * Authors: [[Jonathan Long]], [[Evan Shelhamer]], [[Trevor Darrell]] DOI: 10.1109/CVPR.2015.729 ......
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation * Authors: [[Olaf Ronneberger]], [[Philipp Fischer]], [[Thomas Brox]] Local library 初读 ......
SeaFormer: Squeeze-enhanced Axial Transformer for Mobile Semantic Segmentation
SeaFormer: Squeeze-enhanced Axial Transformer for Mobile Semantic Segmentation * Authors: [[Qiang Wan]], [[Zilong Huang]], [[Jiachen Lu]], [[Gang Yu]] ......
RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation
RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation * Authors: [[Guosheng Lin]], [[Anton Milan]], [[Chunhua Shen]], [[ ......
Expectation-Maximization Attention Networks for Semantic Segmentation 使用了EM算法的注意力
Expectation-Maximization Attention Networks for Semantic Segmentation * Authors: [[Xia Li]], [[Zhisheng Zhong]], [[Jianlong Wu]], [[Yibo Yang]], [[Zho ......
UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery
UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery * Authors: [[Libo Wang]], [[Rui Li]], [[ ......
Context Prior for Scene Segmentation带上下文先验的分割
Context Prior for Scene Segmentation * Authors: [[Changqian Yu]], [[Jingbo Wang]], [[Changxin Gao]], [[Gang Yu]], [[Chunhua Shen]], [[Nong Sang]] DOI: ......
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
UNet++: A Nested U-Net Architecture for Medical Image Segmentation * Authors: [[Zongwei Zhou]], [[Md Mahfuzur Rahman Siddiquee]], [[Nima Tajbakhsh]], ......
Asymmetric Non-Local Neural Networks for Semantic Segmentation 非对称注意力
Asymmetric Non-Local Neural Networks for Semantic Segmentation * Authors: [[Zhen Zhu]], [[Mengdu Xu]], [[Song Bai]], [[Tengteng Huang]], [[Xiang Bai]] ......
PSANet: Point-wise Spatial Attention Network for Scene Parsing双向注意力
PSANet: Point-wise Spatial Attention Network for Scene Parsing * Authors: [[Hengshuang Zhao]], [[Yi Zhang]], [[Shu Liu]], [[Jianping Shi]], [[Chen Cha ......
UIU-Net: U-Net in U-Net for Infrared Small Object Detection：Unet中的Unet
UIU-Net: U-Net in U-Net for Infrared Small Object Detection * Authors: [[Xin Wu]], [[Danfeng Hong]], [[Jocelyn Chanussot]] DOI: 10.1109/TIP.2022.32284 ......
Scale-Prior Deformable Convolution for Exemplar-Guided Class-Agnostic Counting
Scale-Prior Deformable Convolution for Exemplar-Guided Class-Agnostic Counting 初读印象 comment:: （计数用的一个网络）提出了一个标度优先的可变形卷积，将典范的信息，例如标度，整合到计数网络主干中。 动机 本文考 ......
Adaptive Sparse Convolutional Networks with Global Context Enhancement for Faster Object Detection on Drone Images
Adaptive Sparse Convolutional Networks with Global Context Enhancement for Faster Object Detection on Drone Images * Authors: [[Bowei Du]], [[Yecheng ......
A Deformable Attention Network for High-Resolution Remote Sensing Images Semantic Segmentation可变形注意力
A Deformable Attention Network for High-Resolution Remote Sensing Images Semantic Segmentation * Authors: [[Renxiang Zuo]], [[Guangyun Zhang]], [[Rong ......
AWS - Required permissions for a node group role
Before you create worker nodes, you must create an IAM role with the following IAM policies: AmazonEKSWorkerNodePolicy AmazonEKS_CNI_Policy AmazonEC2C ......
1 K8S for Prometheus Dashboard 20211010 EN
* [Prometheus Time Series Collection and Processing Server](http://localhost:9090/targets?search=#pool-prometheus)* [Dashboards | Grafana Labs](https: ......
GCGP：Global Context and Geometric Priors for Effective Non-Local Self-Attention加入了上下文信息和几何先验的注意力
Global Context and Geometric Priors for Effective Non-Local Self-Attention * Authors: [[Woo S]] 初读印象 comment:: （GCGP）提出了一个新的关系推理模块，它包含了一个上下文化的对角矩阵和二维相 ......
maturin 方便发布基于rust 的python 包工具
maturin 是PyO3团队开发的，方便我们开发基于rust 的python 包，比如PyO3 的使用文档中就使用了此工具 安装&使用 安装(可选，可以基于venv 安装) 可以基于pip 以及pipx pipx install maturin 创建一个简单项目 python -m venv .v ......
Rethinking and Improving Relative Position Encoding for Vision Transformer: ViT中的位置编码
Rethinking and Improving Relative Position Encoding for Vision Transformer * Authors: [[Kan Wu]], [[Houwen Peng]], [[Minghao Chen]], [[Jianlong Fu]], ......
js中结束多层for循环
关键字break和continue都是结束循环的作用，但是它只能结束它外面的第一层循环，如果代码里面是一层一层又一层的循环，你想直接结束最外层循环就需要outer了。 outer:for (int i = 0; i < 10; i++) { for (int j = 0; j < 10; j++) ......
Educational Codeforces Round 131 (Rated for Div. 2)
基本情况 AB秒了。C知道是二分答案，check死活写不出来。 C. Schedule Management Problem - C - Codeforces 错误分析 这题比较绕，搞了一个对应关系，大脑转不过来。 写check的时候完全想不出合理的思路。 很明显的要用桶来计数，但是怎么用不知道了。 ......
汇编-LOOPZ和LOOPE指令
LOOPE(相等循环)指令等价于LOOPZ 这两条指令执行如下任务：ECX=ECX-1若ECX >0且ZF=1，则跳转到目的地址;否则结束循环 LOOPZ和LOOPE不影响任何状态标志 在32位模式下， ECX是循环计数器； 在64位模式下， RCX是循环计数器。 ......
神经网络优化篇：机器学习基础（Basic Recipe for Machine Learning）
机器学习基础 下图就是在训练神经网络用到的基本方法：（尝试这些方法，可能有用，可能没用） 这是在训练神经网络时用到地基本方法，初始模型训练完成后，首先要知道算法的偏差高不高，如果偏差较高，试着评估训练集或训练数据的性能。如果偏差的确很高，甚至无法拟合训练集，那么要做的就是选择一个新的网络，比如含有更 ......
cargo-make rust 任务执行以及构建工具
再学习nakago 框架的时候发现其使用了cargo-make 这个工具，但是很方便，类似make 的构建模式 包含的特性 依赖管理，别名支持，支持workspace 简单使用 安装 cargo install --force cargo-make 参考使用 创建一个cargo 项目 cargo n ......
nakago 轻量级rust 框架
nakago 轻量级rust 框架，还处于早期阶段 包含的特性 依赖注入 基于Axum 的http adapter 基于seaORM 的sql adapter 基于async_graphql 的graphql adapter 基于CQRS-ES 的CQRS adapter （即将实现） 说明 nak ......
com.mysql.cj.jdbc.exceptions.MysqlDataTruncation: Data truncation: Incorrect datetime value: '1' for column 'date' at row 1
出现 com.mysql.cj.jdbc.exceptions.MysqlDataTruncation: Data truncation: Incorrect datetime value: '1' for column 'date' at row 1错误数据库中的daka表字段 date ，原本初 ......
Conv2Former: A Simple Transformer-Style ConvNet for Visual Recognition：使用大核卷积调制来简化注意力
Conv2Former: A Simple Transformer-Style ConvNet for Visual Recognition * Authors: [[Qibin Hou]], [[Cheng-Ze Lu]], [[Ming-Ming Cheng]], [[Jiashi Feng]] ......
MetaFormer Is Actually What You Need for Vision：通用的ViT架构才是关键
MetaFormer Is Actually What You Need for Vision * Authors: [[Weihao Yu]], [[Mi Luo]], [[Pan Zhou]], [[Chenyang Si]], [[Yichen Zhou]], [[Xinchao Wang]] ......