stuff 39 path for
Educational Codeforces Round 160 (Rated for Div. 2)
比赛录屏 \(A. Rating Increase\) https://codeforces.com/contest/1913/submission/237734923 \(B. Swap and Delete\) https://codeforces.com/contest/1913/submis ......
LightGCL Simple Yet Effective Graph Contrastive Learning For Recommendation论文阅读笔记
Abstract 目前的图对比学习方法都存在一些问题，它们要么对用户-项目交互图执行随机增强，要么依赖于基于启发式的增强技术（例如用户聚类）来生成对比视图。这些方法都不能很好的保留内在的语义结构，而且很容易受到噪声扰动的影响。所以我们提出了一个图对比学习范式LightGCL来减轻基于CL的推荐者的通 ......
ModuleNotFoundError: No module named 'xxx'
一、原因 未下载或下载失败对应module 二、解决 pip install xxx 添加下载源可参考Mac安装Anaconda3 ......
Educational Codeforces Round 132 (Rated for Div. 2)
基本情况 AB秒了。C跨度有点太大，题解暂时都还没理解。 C. Recover an RBS Problem - C - Codeforces 待补题 ......
BigdataAIML-ML-Models for machine learning Explore the ideas behind machine learning models and some key algorithms used for each
最好的机器学习教程系列：https://developer.ibm.com/articles/cc-models-machine-learning/ By M. Tim Jones, Published December 4, 2017 Models for machine learning Alg ......
Relation Networks for Object Detection
Relation Networks for Object Detection * Authors: [[Han Hu]], [[Jiayuan Gu]], [[Zheng Zhang]], [[Jifeng Dai]], [[Yichen Wei]] DOI: 10.1109/CVPR.2018.0 ......
Deep Residual Learning for Image Recognition：ResNet
Deep Residual Learning for Image Recognition * Authors: [[Kaiming He]], [[Xiangyu Zhang]], [[Shaoqing Ren]], [[Jian Sun]] DOI: 10.1109/CVPR.2016.90 初读 ......
Local Relation Networks for Image Recognition： LRNet
Local Relation Networks for Image Recognition * Authors: [[Han Hu]], [[Zheng Zhang]], [[Zhenda Xie]], [[Stephen Lin]] DOI: 10.1109/ICCV.2019.00356 @in ......
SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation
SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation * Authors: [[Meng-Hao Guo]], [[Cheng-Ze Lu]], [[Qibin Hou]], [[Zhengning ......
CCNet: Criss-Cross Attention for Semantic Segmentation
CCNet: Criss-Cross Attention for Semantic Segmentation * Authors: [[Zilong Huang]], [[Xinggang Wang]], [[Yunchao Wei]], [[Lichao Huang]], [[Humphrey S ......
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 ......
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]], [[ ......
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]] ......
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 ......
39道C++内存管理高频题整理(附答案背诵版)
### 内存管理基础 请解释堆和栈的区别是什么？ 堆（Heap）和栈（Stack）是C++中用于内存分配的两个重要概念。它们的主要区别在于管理方式、使用方式和存储特性。 1. **管理方式**: - **栈**: 自动管理。当函数调用时，局部变量会自动分配在栈上。函数执行完毕后，这些变量会自动释放。 ......
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 ......
题解 LGP7294【[USACO21JAN] Minimum Cost Paths P】/ accoders::NOI 5696【棋子】
problem Farmer John 的牧草地可以看作是一个\(N×M\)（\(2≤N≤10^9, 2≤M≤2⋅10^5\)）的正方形方格组成的二维方阵（想象一个巨大的棋盘）。对于 \(x∈[1,N],y∈[1,M]\)，从上往下第 \(x\) 行、从左往右第 \(y\) 列的方格记为 \((x, ......
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: ......