数据调试

cdeepfuzz networks reading testing

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 ......
super-read-only running 办法 server option

如何在谷歌 Google Chrome 浏览器禁用掉右键菜单中的【使用朗读模式 Reading Mode 打开】

如图1： 如图2（需要重启 Chrome）： 谢谢浏览！ ......
菜单 浏览器 Reading 模式 Google

Test

<p style="text-align: center;">欢迎来到我的友链小屋</p><div class="friendsbox"><div id="app"><h6 style="text-align: center; color: #2daebf;">展示本站所有友情站点，排列不分先后，均 ......
Test

ssh远程到目标主机报错：ssh_exchange_identification: read: Connection reset by peer 问题的处理

问题描述 通过ssh连接到目标主机，报错如下: #ssh 10.192.121.202 ssh_exchange_identification: read: Connection reset by peer 问题分析 通过报错的信息可以看到，连接是被目标的主机给断了。 问题解决 在网上找了一些解决的 ......
ssh_exchange_identification identification Connection ssh exchange

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 ......
network_mode network 模式 Docker 网络

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" ......
quot port_bindings network_mode incompatible bindings

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

ATM1.0面条版test

【一】功能概要 【1】注册 【2】登陆 【3】取款 【4】存款 【5】查看流水 【6】查看银行信息(查看自己的卡号、余额) 【7】初始化银行信息 【8】退出 【二】功能需求 【1】注册 （1）身份信息构成 身份信息包括：用户名、密码、角色 （2）参数验证 验证用户名是未注册过的用户名 验证密码为三位 ......
面条 ATM1 test ATM

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

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

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

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

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

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

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

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

boost beast http::read 一直阻塞不返回,问题解决, 使用parser对象的skip(true) 来解决

用beast 作为客户端发送http请求后读web服务端返回的数据，遇到了http::read 或http::async_read一直阻塞着，不返回，直到连接过期后被强制网络断开后read函数才返回。 看了官方文档，文档里这么描述的，read要一直等到end_of_stream时才回退出阻塞状态。也 ......
对象 parser 问题 boost beast

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

电脑时间不同步导致的上网报错：core/proxy/vmess/encoding: failed to read response header > websocket: close 1006 (abnormal closure): unexpected EOF

报错内容： 2023/12/16 14:08:56 [Warning] [775541588] xxxxx.com/core/app/proxyman/outbound: failed to process outbound traffic > xxxxx.com/core/proxy/vmess/ ......
unexpected websocket abnormal encoding response

基因组序列比对（read alignment）

基因组序列比对（read alignment）技术，是将测序得到的read与已有的参考基因组进行比对，找到read与参考基因组匹配的对应位置，继而得到序列比对的详细结果。 由于参考基因组碱基数极多，测序得到的read数据量极大，且测序的DNA序列中存在各种碱基变异和测序错误，因此不能直接将read与 ......
基因组 序列 基因 alignment read
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