configured for running network
MySQL server is running with the --super-read-only option的解决办法
原因 数据库是只读模式 解决办法 修改为读写模式 mysql -uroot -p你的密码 进入mysql select @@read_only; set global read_only=0; # 顺便设置可远程连接(不需要可跳到flush privileges) use mysql; update ......
CentOS7 yum错误:One of the configured repositories failed (Unknown)
一、现象 二、原因 可能会有其他原因造成该问题(如,网络问题)。我这边的问题是红框中指定镜像重复,导致yum命令执行失败。 三、解决 cd /etc/yum.repos.d 排查重复的repo并将其删除。 ......
CF1861C-Queries-for-the-Array-题解
title: CF1861C Queries for the Array 题解 date: 2023-09-06 07:53:53 categories: - 题解 因为插入和删除操作都在队尾,所以对序列前缀分析一下: 若一个序列的答案为 YES,那么它前缀的答案也为 YES。(对于没检查过的序列) ......
Educational Codeforces Round 160 (Rated for Div. 2) 题解A~D
Educational Codeforces Round 160 (Rated for Div. 2) A. Rating Increase 纯暴力,分割字符串,如果n1<n2就输出,如果遍历完整个数组都不存在n1<n2就输出-1. const int N = 2e5 + 10; int toint ......
配置内核的时候提示Your display is too small to run Menuconfig! It must be at least 19 lines by 80 columns.
按照按照 (https://rocketboards.org/foswiki/Documentation/EmbeddedLinuxBeginnerSGuide)制作了一个image当想打开内核kernel的配置界面make ARCH=arm menuconfig的时候提示: scripts/kco ......
.Net6 Unable to configure HTTPS endpoint. No server certificate was spec 开发者证书过期或无效
1.删除无效的证书 右键都删除 2.cmd窗口输入以下命令 dotnet dev-certs https dotnet dev certs https--trust 3.附其他 dotnet dev-certs https --clean 清理开发人员证书命令 ......
Educational Codeforces Round 160 (Rated for Div. 2) A~C
A. Rating Increase 题意: 将一个字符串分成两个整数a和b,要求没有前导0,且a < b 思路: 遍历字符串s,若当前位置不是0,则拆分字符串,比较大小 // #include <bits/stdc++.h> #include <iostream> #include <string ......
Educational Codeforces Round 160 (Rated for Div. 2)
基本情况 A题秒了。 B题卡了实在太久,BC题最后虽然都过了,但是耗时太久。感觉C对我来说更好写。 B. Swap and Delete 经典+3。 总是一条路偏要走到黑了才会想着换思路,早该换了。 一开始想了一大堆乱七八糟的思路,但都错了。 后面往简单了想,这题毕竟最后必须要左对齐的,直接从左往右 ......
ubuntu 18.04.6编译uboot提示error: bad value (‘generic-armv7-a’) for ‘-mtune=’ switch
按照按照 (https://rocketboards.org/foswiki/Documentation/EmbeddedLinuxBeginnerSGuide)制作了一个image当编译uboot的时候, 发送命令make: make socfpga_cyclone5_config make 得到 ......
Queries for the Array 题解
前言 这场 CF 是我赛后打的,vp 赛时没做出来,后来发现是有个地方理解错了,有一些细节没有考虑到。现在换了一种思路来写,感觉更清晰了。 做法 首先需要动态维护三个变量,\(cnt\) 和 \(finishsort\) 和 \(unfinishsort\)。这三个变量分别表示当前数字的个数,已经排 ......
Sw-YoloX An anchor-free detector based transformer for sea surface object detection
Sw-YoloX An anchor-free detector based transformer for sea surface object detection 基于Transformer用于海上目标检测的无锚检测器:Sw-YoloX 1)由于不同海洋状态下的活体和漂浮物体数据稀缺且昂贵,我们 ......
Access denied for user 'root'@'%' to database 'information_schema'
原因 information_schema是一个虚拟的数据库,里面的表其实都是视图。应切换数据库为“真正的数据库” 解决 USE `THE-REAL-DATABASE`; ......
Docker网络模式--network_mode
docker-compose.yml 配置文件中的 network_mode 是用于设置网络模式的,与 docker run 中的 --network 选项参数一样的,可配置如下参数: 一、bridge **默认 **的网络模式。如果没有指定网络驱动,默认会创建一个 bridge 类型的网络。 桥接 ......
Docker error: "host" network_mode is incompatible with port_bindings
原因 这个错误的原因是在Docker的配置中,使用了"host"网络模式,同时又试图绑定端口(port_bindings)。"host"网络模式意味着容器将直接使用主机的网络,而不是使用Docker创建的虚拟网络。在这种模式下,容器的网络栈不会被隔离,容器可以直接监听主机的网络端口。 因此,当使用" ......
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 ......
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 ......
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 ......
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 ......
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 ......
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 ......
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 ......
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 ......
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 ......
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]], [[ ......