Comparison 第10页

[循证理论与实践] Meta分析系列之六：间接比较及网状 Meta 分析

1、间接比较Meta分析间接比较（indirectcomparison）是指通过干预措施Avs.C和干预措施Bvs.C的结果，间接得出Avs.B的相对效果的一种方法

amw5181360·2022-12-31 11:25

pandas 错误提醒：FutureWarning: elementwise comparison failed;

背景在数据处理时，对原始数据进行筛选操作，在不注意情况下，会引发FutureWarning:elementwisecomparisonfailed;returningscalarinstead,butinthefuturewillperformelementwisecomparison

数据人阿多·2022-12-29 15:36

风格迁移篇---SAnet：风格注意网络下的任意风格转换

NetworkArchitecture3.2.SANetforStyleFeatureEmbedding3.3.FullSystem4.ExperimentalResults4.1.ExperimentalSettings4.2.ComparisonwithPriorWork4.3

啊菜来了·2022-12-29 12:33

SLAM中位姿估计的图优化方法比较

AComparisonofGraphOptimizationApproachesforPoseEstimationinSLAM作者：AndelaJuric´,FilipKendeš,IvanMarkovic

Tom Hardy·2022-12-29 11:36

夸奖的方法

这里还有一个夸奖的方法——FFC法：Feel-感受，用情绪化的语言表达感受；Fact-事实，把赞美部分具体化；Comparison-比较，通过比较优势来表达深度认同。

tyx田·2022-12-28 20:09

什么是优化问题 Optimization Problem

Maximizingorminimizingsomefunctionrelativetosomeset,oftenrepresentingarangeofchoicesavailableinacertainsituation.Thefunctionallowscomparisonofthedifferentchoicesfordeterminingwhich

TriAzure·2022-12-27 08:57

堆排序

堆排序Incomputerscience,heapsortisacomparison-basedsortingalgorithm.Heapsortcanbethoughtofasanimprovedselectionsort

Clusm·2022-12-27 08:51

python 条形图 stack_使用Pandas DataFrames在Python中绘制条形图

TheabilitytorenderabarplotquicklyandeasilyfromdatainPandasDataFramesisakeyskillforanydatascientistworkinginPython.Nothingbeatsthebarplotforfastdataexplorationandcomparisonofvar

袁犬·2022-12-25 18:06

深度学习——day42：基于M-B-LSTM混合网络的短期交通流预测方法

chap1INTRODUCTONAContributionschap3M-B-LSTMA.DataMappingLayerB.StochasticityReducingLayerC.ForecastingLayerD.NetworkTrainingchap4EXPERIMENTSD.ComparisonExperimentsandDiscus

想太多!·2022-12-24 19:28

论文阅读：Objects as Points（也叫CenterNet）

中心点正负样本的标定以及改进的focalloss5、宽高和总体的损失函数6、Frompointstoboundingboxes7、不同basenet和augmentation下的网络性能8、State-of-the-artcomparison9

贾小树·2022-12-24 11:52

利用LSTM识别显式篇章关系实战可作为毕设

本教程通过一个在pdtb体系第一层（pdtb数据将篇章关系分为三个层次，在第一层大体上分为四类，包含Comparison、Contingency、E

数学是算法的灵魂·2022-12-23 05:12

＜＜视觉问答＞＞2022：MuKEA: Multimodal Knowledge Extraction and Accumulation for Knowledge-based VQA

MultimodalKnowledgeTripletExtraction3.2、KnowledgeTripletRepresentationLearning3.3、KnowledgeAccumulationandPrediction四、Experiments4.1、ComparisonwithState-of-the-A

金克丝、·2022-12-22 16:59

【paper笔记】Long-tail Session-based Recommendation 基于长尾的会话推荐

0ABSTRACT1INTRODUCTION2MODEL2.1Notations2.2PreferenceMechanism2.3SessionPoolingandSoftAdjustment3EXPERIMENTS4RESULTSANDANALYSIS4.1ComparisonwithBaselineMethods4.2TheEffectofSoftAdjustment4.3Appl

天南浅蓝·2022-12-22 06:28

风格迁移篇--CCPL：Contrastive Coherence Preserving Loss for Versatile Style Transfer多功能风格转换的对比连贯保持损失

Abstract1Introduction2RelatedWorks3Methods3.1ContrastiveCoherencePreservingLoss3.2SimpleCovarianceTransformation3.3LossFunction4Experiments4.1Experimentalsettings4.2ComparisonwithFormerMethods4.3A

啊菜来了·2022-12-22 06:57

Unity渲染在所有层之上的shader

PerRendererData]_MainTex("SpriteTexture",2D)="white"{}_Color("Tint",Color)=(1,1,1,1)_StencilComp("StencilComparison

沈夕林·2022-12-19 22:46

dRep学习笔记

MrOlm/drep:Rapidcomparisonanddereplicationofgenomeshttps://blog.csdn.net/weixin_45552562/article/details

cling5899·2022-12-19 13:21

论文笔记【场景文字识别】What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis

〇、前言WhatIsWrongWithSceneTextRecognitionModelComparisons?

郭汪汪·2022-12-18 10:06

MICCAI 2022 | CLFC:基于对比学习的多模态脑肿瘤分割与单模态正常脑图像的特征比较

CLFC基于对比学习的多模态脑肿瘤分割与单模态正常脑图像的特征比较MultimodalBrainTumorSegmentationUsingContrastiveLearningBasedFeatureComparisonwithMonomodalNormalBrainImages

Jorko的浪漫宇宙·2022-12-18 07:45

求解常和偏微分方程的人工神经网络

文章目录系列文章目录前言一、背景介绍二、方法描述1.梯度计算三、方法说明1单元常微分方程与多元常微分方程2SolutionofsinglePDEs四、例子4.1ODEsandsystemsofODEs4.2PDEs4.3ComparisonwithFin

一根黄三·2022-12-15 06:03

Y分钟速成SQL

不同的实现通常会添加特有的语言扩展;[不同SQL实现的比较(ComparisonofdifferentSQLimplementat-ions)](http://troels.arvin.dk/db/rdbms

·2022-12-14 14:59

DC-UNet: Rethinking the U-Net Architecture with Dual Channel Efficient CNN for Medical Images Segmen

DC-UNet1MainContribution2Datasets3DataAugment4Initialization5ComparisonRange6Measurementmetric7ResultsofComparison7.1Resultsofinfraredbreastimages7.2Resultsofelectronmicroscopyimage7.3Resultsofendosco

Philo`·2022-12-14 03:04

【目标检测论文精读】……YOLO-V1 ……(You Only Look Once: Unified, Real-Time Object Detection)

文章目录Abstract（摘要）Introduction（引言）UnifiedDetection（统一的目标检测）ComparisontoOtherDetectionSystems（和其他模型对比）Experiments

深度不学习！！·2022-12-12 19:11

数据结构（十）：排序（直接/折半插入排序、希尔排序、冒泡排序、快速排序）

目录一、直接插入排序二、折半插入排序三、希尔排序四、冒泡排序五、快速排序一、直接插入排序●直接插入排序的动画演示详见：ComparisonSortingVisualization●原理：初始的L[1]可视为一个已经排好序的子序列查找出

ReadyGo!!!·2022-12-11 23:30

数据结构（十一）：排序（简单选择排序、堆排序、归并排序）

目录一、简单选择排序二、堆排序三、归并排序一、简单选择排序●简单选择排序的动画演示详见：https://www.cs.usfca.edu/~galles/visualization/ComparisonSort.html

ReadyGo!!!·2022-12-11 23:30

论文阅读 Soft-Demapping for Short Reach Optical Communication: A Comparison of Deep Neural Networks and

这篇文章比较了相干系统中DNN和Volterra算法，系统主要损伤是器件非线性。摘要：在光纤通信系统中，光电器件都会引入非线性，因此需要有效方案对高速信号进行补偿，特别在短距通信中，器件是最大的非线性来源。Volterra是在接收端均衡器件非线性和缓解记忆效应的主流技术，但是Volterra非常复杂。这篇文章研究了软解码DNN，作为非线性均衡和软判决解映射的替代方法。在相干92Gbaud双偏振64

Zaгathustra·2022-12-11 05:10

Lecture 11: ConvNets for NLP

convolutionfortextSingleLayerCNNforSentenceClassificationModelcomparison:OurgrowingtoolkitVeryDeepConvolutionalNetworksforTextClassifi

24kb_·2022-12-10 06:58

最优传输论文（六十三）：Contrastive Adaptation Network for Unsupervised Domain Adaptation论文原理

CtrlZ1·2022-12-10 04:12

【论文速读】基于投影方法的激光雷达点云处理比较

文章：LiDARpoint-cloudprocessingbasedonprojectionmethods:acomparison作者：GuidongYang,SimoneMentasti,MattiaBersani

Being_young·2022-12-08 13:47

李宏毅机器学习笔记—第二节—General Guidance

目录Lossontrainingdata——large1.modelbias2.optimization3.Solution1.Gainingtheinsightsfromcomparison2.Startfromshallowernetworks

菅田将暉_·2022-12-06 11:34

CS和MRA算法

参考文献：ACriticalComparisonAmongPansharpeningAlgorithmsCS（componentsubstitution,成分替换）将MS分为空间分量和光谱分量，用PAN

CCRJ·2022-12-05 22:25

FutureWarning: elementwise comparison failed； returning scalar instead, but in the future will……

项目场景：读取遥感影像问题描述FutureWarning:elementwisecomparisonfailed;returningscalarinstead,butinthefuturewillperformelementwisecomparisonifim_data

编程小白why·2022-12-05 00:46

MPViT : Multi-Path Vision Transformer for Dense Prediction

MPViT:Multi-PathVisionTransformerforDensePrediction一、引言（一）、VisionTransformersfordensepredictions（二）、ComparisontoConcurrentwork

小小小~·2022-12-04 20:11

A Comparison of Super-Resolution and Nearest Neighbors Interpolation Applied to Object Detection

参考AComparisonofSuper-ResolutionandNearestNeighborsInterpolation-云+社区-腾讯云摘要超分辨率(SR)作为一个成熟的研究课题，已经被应用于图像重建之外的其他领域

Wanderer001·2022-12-03 08:16

字符识别

文章目录CRNNRAREESIRWhatIsWrongWithSceneTextRecognitionModelComparisons?

进击的煎饼果子·2022-12-02 06:25

SSEGCN

InputandEncodingLayerAttentionLayerAspect-awareAttentionSelf-AttentionSyntax-MaskLayerGCNLayerTraining4.实验效果DatasetsImplementationDetailsBaselineComparisonsMainResultsAbl

云霄6166·2022-12-01 04:08

论文阅读：迭代CT重建中线性插值模型的比较

AcomparisonoflinearinterpolationmodelsforiterativeCTreconstruction目标：最近的研究表明，基于模型的迭代重建方法可以改善计算机断层扫描(CT

！呜呼啦呼！·2022-11-30 18:15

自编码器/autoencoder

VAE源代码：pytorch实现mnist生成，loss=重构+KL另一份关于VAE进行图像生成+图像定位/分割的源代码：[tensorflow,MNIST,有对各个步骤的详细介绍]—ORSPaired-Comparisons

xys430381_1·2022-11-30 07:58

When Machine Learning Meets Congestion Control: A Survey and Comparison

机器学习邂逅拥塞控制：一个对比性研究论文简介：此论文是一篇综述性的文章，通过阅读本论文可以对拥塞控制算法有一个较为清晰的认识，区分传统算法及辨识各种传统算法的优劣，特别是本文通过导引的方式可以让读者了解机器学习在拥塞控制算法中的应用现状，对应该使用哪种机器学习的方法给读者指明了方向，并使得读者认识到应用RL在CC中的优劣势及面临的挑战。WhenMachineLearningMeetsCongest

嘿喵井长·2022-11-29 03:31

IMPROVE OBJECT DETECTION WITH FEATURE-BASED KNOWLEDGE DISTILLATION: TOWARDS (2021 ICLR)----论文和博客读书笔记

IMPROVEOBJECTDETECTIONWITHFEATURE-BASEDKNOWLEDGEDISTILLATION:TOWARDSACCURATEANDEFFICIENTDETECTORSABSTRACTRELATEDWORKComparisonbetweentheproposedattention-guideddistillationandothermethods.METHODOLOGYA

落了一地秋·2022-11-26 21:30

信号处理深度学习机器学习_机器学习与信号处理

(Afuncomparisonofmachinelearningperformancewithtwokeysignalprocessingalgorithms—theFastFourierTransformandtheLeastMeanSquaresprediction

weixin_26752765·2022-11-26 01:06

李宏毅DLHLP.18.BERT and its family.2/2.ELMo,BERT,GPT,XLNet,MASS,BART,UniLM,ELECTRA

Self-supervisedLearningPredictNextTokenPredictNextToken-BidirectionalMaskingInput几种MASK的方法XLNetMASS/BARTInputCorruptionUniLMELECTRASentenceLevelT5–Comparison

oldmao_2000·2022-11-25 15:41

PyMC3 Developer Guide¶

PyMC3isaPythonpackageforBayesianstatisticalmodelingbuiltontopofTheano.ThisdocumentaimstoexplainthedesignandimplementationofprobabilisticprogramminginPyMC3,withcomparisonstootherPPL

muren2016·2022-11-25 06:49

自监督学习系列(2) SimSiam: Exploring Simple Siamese Representation Learning

FancyCode Artist·2022-11-25 00:39

[Transformer]MAE:Masked Autoencoders Are Scalable Vision Learners

AbstractSectionIIntroductionSectionIIRelatedWorkSectionIIIMethodSectionIVImageNetExperimentsPart1MainPrepertiesPart2ComparisonResultsSectionVTransferLearningSectionVIDiscussionandConclus

黄小米吖·2022-11-24 10:36

树莓派无人机开发指南之一：系统篇

树莓派版本从2012年开始至今发展了很多代，最新的是RaspberryPi4B，已经自带GPU，功能很强大，各版本的详细参数对比可以参考：https://socialcompare.com/en/comparison

cloudkernel-tech·2022-11-23 23:03

图像分割（四）—— Is Space-Time Attention All You Need for Video Understanding?

TimeformerAbstract1.Introduction2.RelatedWork3.TheTimeSformerModel4.Experiments4.1.AnalysisofSelf-AttentionSchemes4.2.Comparisonto3DCNNsAbstract

黑洞是不黑·2022-11-23 07:43

Is Space-Time Attention All You Need for Video Understanding?

AnalysisofSelf-AttentionSchemes4.2.VaryingtheNumberofTokensinSpaceandTime4.3.TheImportanceofPretrainingandDatasetScale4.4.Comparisont

h137437·2022-11-23 07:36

论文阅读|Uniformer

/2201.09450目录AbstractIntroductionMethodOverviewofuniformerblockMulti-headRelationAggregatorLocalMHRAComparisonto3DConvolutionBlockGlobalMHRAComparisontoTransformerBlockDynamicPosi

xiaoweiyuya·2022-11-23 04:23

【论文-Cobb angle】- ing

우 유·2022-11-22 22:05

FVM implementation and analysis of borehole Poroelastic problem of mode3

FVMimplementationandanalysisofboreholePoroelasticproblemofmode3ThisblogwillshowthecomparisonofthenumericalsolutioncalculatedusingFVMcodewiththeanalyticalsolutioninCheng.H.D

weixin_42254787·2022-11-22 13:04

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