数据调试

powerful networks spectral neural

power query合并查询（VLOOKUP功能相似）

合并查询原理 功能：与EXCEL中的VLOOKUP函数（=VLOOKUP（查询条件，查询范围，精确“0”还是模糊“1”匹配））功能相似，根据A表中的条件从B表中找到对应的数据，并根据一定的匹配规则提取该部分数据到A表中； 一、单条件合并查询 定义：选取表一中的一列作为条件，与表二中的单一对应列匹配的 ......
VLOOKUP 功能 power query

BIgdataAIML-IBM-A neural networks deep dive - An introduction to neural networks and their programming

https://developer.ibm.com/articles/cc-cognitive-neural-networks-deep-dive/ By M. Tim Jones, Published July 23, 2017 Neural networks have been around f ......
networks neural BIgdataAIML-IBM-A introduction BIgdataAIML

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 ......
Detection Relation Networks Object for

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 ......
Recognition Relation Networks Local Image

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 ......
Segmentation 注意力 Attention Network Scene

Squeeze-and-Excitation Networks：SENet，早期cv中粗糙的注意力

Squeeze-and-Excitation Networks * Authors: [[Jie Hu]], [[Li Shen]], [[Samuel Albanie]], [[Gang Sun]], [[Enhua Wu]] Local library 初读印象 comment:: (SENet ......
Squeeze-and-Excitation 注意力 Excitation Networks Squeeze

Non-local Neural Networks 第一次将自注意力用于cv

Non-local Neural Networks * Authors: [[Xiaolong Wang]], [[Ross Girshick]], [[Abhinav Gupta]], [[Kaiming He]] Local library 初读印象 comment:: (NonLocal)过去 ......
注意力 Non-local Networks 第一次 Neural

Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network

Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network * Authors: [[Wenzhe Shi]], [[Jose Caballer ......
Super-Resolution Convolutional Resolution Real-Time Efficient

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 ......
convolutional segmentation networks semantic Fully

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 ......
Convolutional Segmentation Biomedical Networks U-Net

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]], [[ ......
High-Resolution Segmentation Multi-path Refinement Resolution

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 ......
Expectation-Maximization Maximization Segmentation 算法 Expectation

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]] ......
Segmentation 注意力 Asymmetric Non-Local Networks

Pyramid Scene Parsing Network

Pyramid Scene Parsing Network * Authors: [[Hengshuang Zhao]], [[Jianping Shi]], [[Xiaojuan Qi]], [[Xiaogang Wang]], [[Jiaya Jia]] DOI: 10.1109/CVPR.20 ......
Pyramid Parsing Network Scene

PIDNet: A Real-time Semantic Segmentation Network Inspired by PID Controllers

PIDNet: A Real-time Semantic Segmentation Network Inspired by PID Controllers * Authors: [[Jiacong Xu]], [[Zixiang Xiong]], [[Shankar P. Bhattacharyya ......
Segmentation Controllers Real-time Inspired Semantic

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 ......
双向 注意力 Point-wise Attention Network

Object Tracking Network Based on Deformable Attention Mechanism

Object Tracking Network Based on Deformable Attention Mechanism Local library 初读印象 comment:: （DeTrack）采用基于可变形注意力机制的编码器模块和基于自注意力机制的编码器模块相结合的方式进行特征交互。基于 ......
Deformable Attention Mechanism Tracking Network

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 ......
Convolutional Enhancement Detection Adaptive Networks

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 ......
High-Resolution Segmentation 注意力 Deformable Resolution

使用 Power Shell 修改 Hyper-V 虚拟机 UUID 的解决方案

在研究了一下午 k8s 文档的时候，正准备开干，万万没想到一个 uuid 的问题卡了我几个小时，一直想在系统中解决，没想到最后在外部使用PowerSheel解决了，分享记录一二 ......
解决方案 Hyper-V 方案 Power Hyper

SiReN Sign-Aware Recommendation Using Graph Neural Networks论文阅读笔记

Abstract 目前使用GNN的推荐系统主要利用高评分的正向用户-物品交互信息。但是如何利用低评分来表示用户的偏好是一个挑战，因为低评分仍然可以提供有用的信息。所以在本文中提出了基于GNN模型的有符号感知推荐系统SiReN，SiReN有三个关键组件 构造一个符号二部图更精确的表示用户的偏好，分为两 ......
Recommendation Sign-Aware Networks 笔记 Neural

Fully Attentional Network for Semantic Segmentation：FLANet

Fully Attentional Network for Semantic Segmentation * Authors: [[Qi Song]], [[Jie Li]], [[Chenghong Li]], [[Hao Guo]], [[Rui Huang]] 初读印象 comment:: (F ......
Segmentation Attentional Semantic Network FLANet

SP21690 POWERUP - Power the Power Up 题解

题目传送门 前置知识 扩展欧拉定理 解法 直接对 \(a\) 和 \(b^c\) 分讨，跑一遍扩展欧拉定理就行了。 另外由于本题的特殊规定 \(0^0=1\)，故需要在当 \(a=0\) 时，对 \(b^c\) 进行判断。手模几组样例，发现结论挺显然的。 代码 #include<bits/stdc+ ......
题解 Power POWERUP 21690 the

SP10050 POWTOW - Power Tower City 题解

题目传送门 前置知识 扩展欧拉定理 解法 本题幂塔是有限层的，这里与 luogu P4139 上帝与集合的正确用法 中的无限层幂塔不同，故需要在到达递归边界 \(n+1\) 时进行特殊处理，对于处理 \(\varphi(p)\) 在递归过程中等于 \(1\) 的情况两题基本一致。 回忆扩展欧拉定理中 ......
题解 POWTOW 10050 Power Tower

【Power Shell】启动时自动配置http代理

背景 有时候我们经常需要在Windows Terminal，powershell内使用http代理来拉去GitHub代码、软件包等等，每次都需要手动配置很麻烦。其实我们可以使用.ps1脚本来启动。 https://learn.microsoft.com/zh-cn/powershell/module ......
Power Shell http

Power BI - 5分钟学习增加索引列

每天5分钟，今天介绍Power BI增加索引列。 什么是增加索引列？增加索引列就是向表中添加一个具有显式位置值的新列，一般从0或者从1开始。 举例：首先，导入一张【Sales】样例表(Excel数据源导入请参考每天5分钟第一天)。 操作步骤：1, 【Home】 -> 【Transform data】 ......
索引 Power BI

PANE-GNN Unifying Positive and Negative Edges in Graph Neural Networks for Recommendation论文阅读笔记

Abstract 目前利用GNN的推荐系统主要关注用户的正面反馈，而忽略了负面反馈提供的见解。于是我们提出了PANG- GNN，该模型将图神经网络的正面和负面边统一在一起。PANG-GNN首先将原始评分图根据正面和负面反馈划分为两个不同的二分图。接下来分别使用两个独立的嵌入，即感兴趣嵌入和无兴趣嵌入 ......
Recommendation PANE-GNN Negative Networks Unifying

CentOS7配置静态ip后service network restart失败

解决方法： 1、检查配置文件，文件夹下是否存在类似文件（ifcfg-ens33），存在的话，删除掉，保留一个即可（判断方式为配置文件中是否有配置信息） cd /etc/sysconfig/network-scripts/ ls 删除命令： rm 文件名称 重启网络：service network r ......
静态 CentOS7 service network restart

Machine is not on the network

在调试Android jni 的时候发现一个奇怪的问题 在连接socket的时候老是报错 m_sock = socket(AF_INET, SOCK_STREAM, 0); if(m_sock < 0) { debug(LEVEL_ERROR, "Socket create error %d\r\n ......
Machine network not the is

使用yarn安装依赖包出现“There appears to be trouble with your network connection. Retrying...”超时的提醒

我们在使用yarn安装依赖包文件的时候，可能会出现“There appears to be trouble with your network connection. Retrying...”超时的提醒，很有可能是因为yarn默认的镜像地址为国外，因此慢（超时）就说得过去了…… 1、问题描述 我们在 ......
connection Retrying appears network trouble
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