526互联

applications approaches extraction learning

[4] Secret Key Extraction using Bluetooth Wireless Signal Strength Measurements 论文精读

近日在找和BLE或者RSS相关的baseline，不好找，找到了一篇2014年的文章，感觉CCF B的文章工作量其实也还好吧。 Secret Key Extraction using Bluetooth Wireless Signal Strength Measurements 题目：通过蓝牙测试R ......
Measurements Extraction Bluetooth Wireless Strength

论文阅读 | Learn from Others and Be Yourself in Heterogeneous Federated Learning

**在异构联邦学习中博采众长做自己** 代码：https://paperswithcode.com/paper/learn-from-others-and-be-yourself-in **摘要** 联邦学习中有异质性问题和灾难性遗忘。首先，由于非I.I.D（相同独立分布）数据和异构体系结构，模型在 ......
Heterogeneous Federated Learning Yourself Others

April 2023-Memory-efficient Reinforcement Learning with Value-based Knowledge Consolidation

本文基于深度q网络算法提出了记忆高效的强化学习算法来缓解这一问题。通过将目标q网络中的知识整合Knowledge Consolidation到当前q网络中，所提算法减少了遗忘并保持了较高的样本效率。 ......
Memory-efficient Consolidation Reinforcement Value-based Knowledge

零样本学习（Zero-shot Learning）

零样本学习是一种机器学习的问题设置，其中模型可以对从未在训练过程中见过的类别的样本进行分类，使用一些形式的辅助信息来关联已见和未见的类别。例如，一个模型可以根据动物的文本描述来识别动物，即使它从未见过那些动物的图像。 实现零样本学习有不同的方法，取决于辅助信息的类型和学习方法。以下是一些例子： 一种 ......
样本 Zero-shot Learning Zero shot

Not on FX application thread; currentThread = pool-3-thread-1

业务线程更新JavaFx的ui界面报错 Not on FX application thread; currentThread = pool-3-thread-1,解决方法很简单，在业务线程里使用Platform.runLater Platform.runLater(()->{ //执行UI更新的代 ......
thread currentThread application pool Not

事件抽取论文综述-A Survey on Deep Learning Event Extraction: Approaches and Applications

A Survey on Deep Learning Event Extraction: Approaches and Applications 1）发表信息： https://arxiv.org/abs/2107.02126 Qian Li, Jianxin Li, Member, IEEE, Ji ......
Applications Approaches Extraction Learning 事件

JAVA restemplate 通过application/x-www-form-urlencoded访问

试了好几种方法都不行，要么返回空，要么报错。最后就这种方法可以返回数据。 MultiValueMap<String, Object> psp = new LinkedMultiValueMap<>(); psp.add("aaa", "xxxxx"); psp.add("bbb", "xxxxxxx ......
x-www-form-urlencoded restemplate application urlencoded JAVA

Planar Odometry from a Radial Laser Scanner. A Range Flow-based Approach（1）论文解读

激光光流里程计的基本理解： （1）类比图像光流，假设光强度不变，图像是每个像素点，像素包含灰度值；激光光流，假设障碍物不动，光流是激光范围内的激光点，每个激光点包含距离和角度信息 （2）图像信息求导，得到光强度；激光光流信息求导，得到速度（距离的速度，角度的速度），并可以用分解到笛卡尔坐标系下的速度 ......
Flow-based Odometry Approach Scanner Planar

循环依赖导致编译或者服务启动报错问题：The dependencies of some of the beans in the application context form a cycle

错误如图: 我的是服务器启动服务时报错： ***************************APPLICATION FAILED TO START*************************** Description: The dependencies of some of the be ......
dependencies application the context 问题

应用启动时加载application.properties配置文件

配置 aliyun.sms.regionId=default aliyun.sms.accessKeyId=LTAIxxx aliyun.sms.secret=PAxxxx import org.springframework.beans.factory.InitializingBean; impo ......
application properties 文件

[论文速览] MAGE@MAsked Generative Encoder to Unify Representation Learning and Image Synthesis

## Pre title: MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis accepted: CVPR2023 paper: https://arxiv.org/abs/221 ......
Representation Generative Synthesis Learning Encoder

[论文阅读] Few-shot Font Generation by Learning Style Difference and Similarity

## Pre title: Few-shot Font Generation by Learning Style Difference and Similarity accepted: Arxiv 2023 paper: https://arxiv.org/abs/2301.10008 code: ......
Difference Generation Similarity Few-shot Learning

[论文速览] RectifiedFlow@Flow Straight and Fast{colon}Learning to Generate and Transfer Data with Rectified Flow

## Pre title: Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow accepted: ICLR 2023 paper: https://arxiv.org/abs/2209 ......
Flow RectifiedFlow Rectified and Learning

NIST SP 800-37 Risk Management Framework for Information Systems and Organizations A System Life Cycle Approach for Security and Privacy

NIST SP 800-37 Risk Management Framework for Information Systems and Organizations A System Life Cycle Approach for Security and Privacy It structured ......
Organizations Information Management Framework for

2023CVPR_Learning a Simple Low-light Image Enhancer from Paired Low-light Instances(PairLLE)无监督

一. motivation 以前的大多数LIE算法使用单个输入图像和几个手工制作的先验来调整照明。然而，由于单幅图像信息有限，手工先验的适应性较差，这些解决方案往往无法揭示图像细节。 二. contribution 1. 提出一个成对低光图像输入（相同内容，不同的曝光度） 2. 在输入之前进行了一个 ......
Low-light light CVPR_Learning Instances Low

learn c++ 函数返回

......
函数 learn

Distributed System and Application

Assignment 2:Distributed System and ApplicationCloud Computing and Distributed Systems (CLOUDS) LaboratorySchool of Computing and Information SystemsT ......
Distributed Application System and

Gartner 魔力象限：应用程序安全测试 2023 - Magic Quadrant for Application Security Testing 2023

Magic Quadrant for Application Security Testing 2023 Gartner 魔力象限：应用程序安全测试 2023 请访问原文链接：，查看最新版。原创作品，转载请保留出处。 作者主页：[sysin.org](https://sysin.org) Gartn ......
象限 2023 Application 应用程序 魔力

SpringBoot 出现 Content type ‘application/x-www-form-urlencoded；charset=UTF-8‘ not supported

``` 问题点1： 如果Content-Type设置为“application/x-www-form-urlencoded;charset=UTF-8”无论是POST请求还是GET请求都是可以通过这种方式成功获取参数，但是如果前端POST请求中的body是Json对象的话，会报上述错误。 请求中传J ......
x-www-form-urlencoded application SpringBoot urlencoded supported

The Difficulty of Passive Learning in Deep Reinforcement Learning

![](https://img2023.cnblogs.com/blog/1428973/202305/1428973-20230524224808789-13684847.png) **发表时间：**2021(NeurIPS 2021) **文章要点：**这篇文章提出一个tandem learni ......
Learning Reinforcement Difficulty Passive Deep

RuntimeError：working outside of application context. Flask使用SQLAlchemy数据库

###问题 报错RuntimeError：working outside of application context. ###本质：依赖包版本不匹配 flask-sqlalchemy、flask-sqlalchemy 版本过高导致，换低版本 ``` pip install flask-sqlalc ......
RuntimeError application SQLAlchemy working outside

learn c++ 参数引用

#include <iostream> struct Role { int hp; int mp; int damage; }; bool Act(Role& Acter,Role& beAct) { beAct.hp -= Acter.damage; return beAct.hp < 0; } ......
参数 learn

LeeeSe/MessAuto: 自动提取Mac平台的短信验证码，2FHey的免费替代品；Automatic extraction of SMS verification code for Mac platform, free alternatives to 2FHey (github.com)

DreamSaddle/MacCopier: MacCopier 是一个提供在 Macos 中收到短信验证码后自动复制到剪贴板功能的软件。 (github.com) LeeeSe/MessAuto: 自动提取Mac平台的短信验证码，2FHey的免费替代品；Automatic extraction o ......
2FHey 替代品 FHey alternatives verification

Learning with Local and Global Consistency

[TOC] > [Zhou D., Bousquet O., Lal T. N., Weston J. and Scholk\ddot{o}pf B. Learning with local and global consistency. NIPS, 2003.](https://proceedin ......
Consistency Learning Global Local with

2023CVPR_Learning a Simple Low-light Image Enhancer from Paired Low-light Instances(PairLIE)

1、nn.ReflectionPad2d 对输入图像以最外围像素为对称轴，做四周的轴对称镜像填充。 大佬链接：(14条消息) torch.nn.ReflectionPad2d()的用法简介_nn.reflectionpad2d(1)_啊菜来了的博客-CSDN博客 # 对四周都填充3行 nn.Refl ......
Low-light light CVPR_Learning Instances Low

[React Typescript] Extracting Props from Custom Components

// Imagine NavBar is an external library! export const NavBar = (props: { title: string; links: string[]; children: React.ReactNode; }) => { return <d ......
Extracting Components Typescript Custom React

Learning Affinity from Attention: End-to-End Weakly-Supervised Semantic Segmentation with Transformers概述

0.前言 相关资料： arxiv github 论文解读 论文基本信息： 领域：弱监督语义分割 发表时间： CVPR 2022(2022.3.5) 1.针对的问题 目前主流的弱监督语义分割方法通常首先训练分类模型，基于类别激活图（CAM）或其变种生成初始伪标签；然后对伪标签进行细化作为监督信息训练一 ......
Weakly-Supervised Segmentation Transformers End-to-End Supervised

learn c++ 智能指针

#include <iostream> int main() { int* p; { std::unique_ptr<int[]> a{std::make_unique<int[]>(50)}; a[2] = 240; p = a.get(); std::cout << p[2]; } std::c ......
指针 智能 learn

Sep 2022-Prioritized Training on Points that are Learnable, Worth Learning, and Not Yet Learnt

提出了Reducible Holdout Loss Selection (RHOLOSS)，一种简单但有原则的技术，近似地选择那些最能减少模型泛化损失的点进行训练 ......
Prioritized Learnable Learning Training Points

C-pointer Learning

# 基础 ## 指针类型 ### 静态/全局内存 指在内存空间中的全局/静态数据区的指针变量 ### 自动内存 即局部作用域的指针，只有在函数被调用时才创建。 ### 动态内存 在堆区动态创建的指针变量，在不使用时需要即是释放该部分内存空间。 ## 特殊指针 ### NULL指针 在指针变量中，初始 ......
C-pointer Learning pointer
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