Experiments】

CenterFusion/src/main.py 项目训练执行文件详解

目录一、train.sh脚本二、main.py文件三、参考资料文件位置：CenterFusion/experiments/train.sh和CenterFusion/src/main.py文件作用：CenterFusion
上班摸不了鱼·2022-12-16 08:23

CenterFusion/src/test.py 项目验证执行文件详解

目录一、test.sh脚本二、test.py文件文件位置：CenterFusion-master/experiments/test.sh和CenterFusion-master/src/test.py文件作用
上班摸不了鱼·2022-12-16 08:23

OCR文本检测模型：FCENet论文阅读笔记

1.介绍（Introduction)2.相关工作（RelatedWork)3.方法（Approach）3.1傅里叶轮廓嵌入（FourierContourEmbedding)3.2FCENet4.实验（Experiments
DU_YULIN·2022-12-16 04:28

【Homography Estimation】《Deep Image Homography Estimation》

arXiv-2016文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method5Experiments5.1Datasets5.2Experiments6Conclusion1BackgroundandMotivation
bryant_meng·2022-12-14 03:02

【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

DiffusionDet: Diffusion Model for Object Detection

Introduction2相关工作RelatedWork3方法Approach3.1预备知识Preliminaries3.2架构Architecture3.3训练Training3.4推理Inference4实验Experiments4.1
明前大奏·2022-12-12 17:13

NLP预训练模型系列-GPT-2

NLP预训练模型系列文章目录前言1.Abstract2.Introduction3.Approach3.1TrainingDataset3.2InputRepresentation3.3Model4.Experiments5
Maxi_0902·2022-12-10 14:13

最优传输论文（三十二）：Deep multi-Wasserstein unsupervised domain adaptation论文原理

文章目录前言摘要1.Introduction2.Relatedwork3.Settingandbackgroundknowledge4.Multi-criticdomainadaptation5.Experiments6
CtrlZ1·2022-12-10 12:08

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

文章目录前言摘要1.Introduction2.RelatedWork3.Methodology3.1.最大平均差异回顾3.2.对比域差异3.3.对比适应网络3.4.OptimizingCAN4.Experiments4.1
CtrlZ1·2022-12-10 04:12

论文阅读笔记（3）——Translating Embeddings for Modeling Multi-relational Data

Abstract1IntroductionModelingmulti-relationaldataRelationshipsastranslationsintheembeddingspace2Translation-basedmodel3Relatedwork4Experiments4.1Datasets4.2Experimentalsetup4.3Linkprediction4.4Learnin
StriveQueen·2022-12-09 15:53

【Cut, Paste and Learn】《Cut, Paste and Learn: Surprisingly Easy Synthesis for Instance Detection》

1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method4.1Collectingimages4.2AddingObjectstoImages4.2.1Blending4.2.2DataAugmentation5Experiments5.1Datasets5.2TrainingandEvalu
bryant_meng·2022-12-09 02:03

【AutoAgument for OD】《Learning Data Augmentation Strategies for Object Detection》

ECCV-2020文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method5Experiments5.1Learningadataaugmentationpolicy5.2Learnedaugmentationpolicysystematicallyimprovesobjectdetection5.3Explo
bryant_meng·2022-12-09 02:02

Spatio temporally Action Detection Location 系列(2) :A Better Baseline for AVA

SpatiotemporallyActionDetectionLocation系列（2）：ABetterBaselineforAVA一简介二ModelandApproach三Experiments：四与
huyouni110·2022-12-08 05:54

【网络安全】红队攻防之基础免杀

注入代码如下：intmain(intargc,char*argv[]){HANDLEprocessHandle;PVOIDremoteBuffer;wchar_tdllPath[]=TEXT("C:\\experiments
kali_Ma·2022-12-06 20:29

pysot出现的问题---AssertionError: /home/pysot-master/siamrpn_r50_l234_dwxcBasketball/img/0001.jpg

系列的文章，在配置pysot中demo已经成功跑通了，但是在使用OTB100数据集运行test.py文件时遇到AssertionError:/home/tao/SiamRPN++/pysot-master/experiments
望外追晚·2022-12-04 00:19

本周的总结

.PositiveAttentionShiftingBlockinfd12.2.NegativeAttentionShiftingBlockinfd22.3.LossFunctions（损失函数）3.Experiments
ZN_daydayup·2022-12-03 08:07

BLIP论文笔记

BootstrappingLanguage-ImagePre-trainingforUnifiedVision-LanguageUnderstandingandGenerationAbstract1.Introduction2.Method2.1MED2.2Pre-trainedObjectives2.3CapFilt3.Experiments4
Tarench·2022-12-02 21:46

NeRV: Neural Representations for Videos

NeuralRepresentationsforVideosAbstract1Introduction2RelatedWork3NeuralRepresentationsforVideos3.1NeRVArchitecture3.2ModelCompression4Experiments4.1DatasetsandImplementationDetails4.2MainResults4
attacking tiger·2022-12-02 11:41

图像处理中的常见resize方法性能比较

2.Experiments使用resize方法对图像进行缩小后放大，分析图像重建的效果。对比的方法包括：opencv：cv2.resize。matlab中的
兮的皮卡丘·2022-12-02 07:07

【交通流预测】《Graph WaveNet for Deep Spatial-Temporal Graph Modeling》论文详解

Methodology1.ProblemDefinition2.GraphConvolutionLayer3.TemporalConvolutionLayer4.FrameworkofGraphWaveNet四、Experiments1
stt-Charon·2022-11-30 06:12

论文翻译：Attentional Feature Fusion

AttentionalFeatureFusion摘要1引言2RelatedWork3.Multi-scaleChannelAttention(多尺度通道的关注)4.注意力特征融合AttentionalFeatureFusion5.Experiments6
Sun_ZD·2022-11-30 06:09

基于SwinTransformer+UNet的遥感图像语义分割

SwinTransformerblock3.3.SpatialInteractionModule3.4.FeatureCompressionModule3.5.RelationalAggregationModule4.Experiments
tzc_fly·2022-11-29 11:25

ORB-SLAM: a Versatile and Accurate Monocular SLAM system---阅读笔记(five)

Experiments不详细介绍试验过程！
雪天枫·2022-11-29 09:13

【推荐系统】【论文阅读笔记】【survey】Hybrid Recommender Systems: Survey and Experiments

一、推荐技术简介：论文链接：https://www.researchgate.net/publication/263377228_Hybrid_Recommender_Systems_Survey_and_ExperimentsCF协同推荐：（用户之间的相关性）对现存的对象的评分或推荐进行汇总，根据用户的评分识别用户之间的共性，并根据用户间的比较生成新的推荐。协作系统中的典型用户配置文件由项目向量
yong_ss·2022-11-29 09:14

浅谈Batch和minibatch

很多论文中，通常在Experiments这一块，会写一下trainingstrategies，其中一定会写到训练采用的Batch_size是XX（如64，32等等），或者是minibatch_size=
luissen·2022-11-29 08:19

Focal Self-attention for Local-Global Interactions in Vision Transformers ( DeiT )

MEthod2.1Modelarchitecture2.2Focalself-attention2.2.1Window-wiseattention2.2.2Complexityanalysis2.3Modelconfiguration3.Relatedwork4.Experiments4.1ImageclassificationonImageNet
CV小Rookie·2022-11-29 07:26

NeRF-SR: High-Quality Neural Radiance Fields using Super-Sampling论文翻译

使用超采样的高质量神经辐射场目录使用超采样的高质量神经辐射场Abstract1.Introduction2、RelatedWork3、Background（Nerf介绍）4、ApproachTrainingTesting5.Experiments5.1
ysh9888·2022-11-28 19:23

变分自动编码器（VAE variational autoencoder）

AutoEncoder变分推断VariationalInference变分自动编码器VariationalAutoEncoder条件变分自动编码器ConditionalVariationalAutoEncoder实验Experiments
BubbleCodes·2022-11-28 13:46

Vision In Transformer——（VIT论文阅读）

TransformersForImageRecognitionAtScale1.摘要（Abstract）2.介绍（Introduction）3.相关工作（RelatedWork）4.方法（Method）4.1.VIT归纳偏置混合架构4.2.微调和更高分辨率实验分析（Experiments
scl52tg·2022-11-28 07:45

数据增强：Simple Questions Generate Named Entity Recognition Datasets

文章目录问题背景一、论文核心二、文章内容三、experiments总结问题背景还是在于方法的创新，虽然是数据增强，但玩出了新花样呀。
等景，不如找景·2022-11-28 07:11

对抗性补丁——day54（second）Towards-a-physical-world-adversarial-patch-for-blinding object detection models

Towards-a-physical-world-adversarial-patch-for-blindingobjectdetectionmodels1.Introduction3.Methodology3.1.Foolingobjectdetectionmodelwithadversarialpatch4.Experiments4.1
qq_43537420·2022-11-28 05:48

李沐老师-《如何读论文》-课堂笔记

论⽂结构：1.title2.abstract3.introduction4.method5.experiments6.conclusion都是从头读到尾，时间是划不来；适合的⽂章可能就是⼀⼩部分，需要快速找到适合的
Annnn~·2022-11-27 07:18

2021-Twins: Revisiting the Design of Spatial Attention

4.1Twins-PCPVT4.2Twins-SVT4.2.1Locally-GroupedSelf-Attention（LSA）4.2.2GlobalSub-SampledAttention（GSA）4.3ModelVariants5.Evaluation5.1Experiments5.2Ablat
小毛激励我好好学习·2022-11-26 18:32

【Focal Loss】《Focal Loss for Dense Object Detection》

1BackgroundandMotivation2Advantages/Contributions/Innovations3RelatedWork4Method4.1FocalLossDefinition4.2RetinaNetDetector5Experiments5.1Datas
bryant_meng·2022-11-25 11:27

【机器翻译】【mRASP】跑通mRASP代码（一）：preprocess

以作者使用的toyen-de数据集微调工作为示例，该数据集作者已经放在了experiments/example/data/raw，这里直接用首先下载代码，配置环境不再赘述，按照开源代码进行接着从linzehui
耶格尔派**·2022-11-25 05:05

ESRGAN: Enhanced 增强的Super-Resolution Generative Adversarial Networks

.1Introduction2RelatedWork3ProposedMethods3.1NetworkArchitecture3.2RelativisticDiscriminator3.3PerceptualLoss3.4NetworkInterpolation4Experiments4.1TrainingDetails4.2Data4.3QualitativeResults
ysh9888·2022-11-25 04:39

SRGAN论文与ESRGAN论文总结

博客结构SRGANContribution：NetworkArchitecture:GeneratorNetworkDiscriminatorNetworkPerceptuallossfunction：Experiments
敲困难的代码猿·2022-11-25 04:08

论文学习-SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers

SimpleandEfficientDesignforSemanticSegmentationwithTransformersAbstract1Introduction2RelatedWork3Method3.1分级Transformer编码器3.2轻量级All-MLP解码器3.3与SETR的关系4Experiments4.1ExperimentalSettings4
ZZE15832206526·2022-11-25 00:59

AN IMAGE IS WORTH 16X16 WORDS: TRANSFORMERS FOR IMAGE RECOGNITION AT SCALE——ViT全文翻译

相关说明基本信息介绍ABSTRACT1INTRODUCTION2RELATEDWORK3METHOD3.1VISIONTRANSFORMER(ViT)3.2FINE-TUNINGADNHIGHERRESOLUTION4EXPERIMENTS4.1SETUP4.2COMPAR
陈嘿萌·2022-11-24 10:42

ICML2018(Anomaly Detection)：Deep SVDD-论文解读《Deep One-Class Classification》

文章目录原文地址论文阅读方法初识相知2.RelatedWork3.DeepSVDD4.Experiments回顾代码原文地址http://data.bit.uni-bonn.de/publications
我是大黄同学呀·2022-11-24 05:36

DAB-DETR:Dynamic Anchor Boxes Are Better Queries for DETR阅读笔记

4.2本文的主要工作4.2.1直接学习anchorboxes4.2.2AnchorUpdate4.2.3Width&Height调制高斯核4.2.4温度系数的调整(五)Experiments(六)Conclusion
不知道叫啥好一点·2022-11-23 23:04

FCOSR: A Simple Anchor-free Rotated Detector for Aerial Object Detection阅读笔记

FCOSR论文阅读笔记(一)Title(二)Summary(三)Method3.1网络输出3.2椭圆中心采样3.3Fuzzysamplelabelassignment3.4多阶段采样3.5损失函数(四)Experiments4.1
不知道叫啥好一点·2022-11-23 21:02

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

TimeformerAbstract1.Introduction2.RelatedWork3.TheTimeSformerModel4.Experiments4.1.AnalysisofSelf-AttentionSchemes4.2
黑洞是不黑·2022-11-23 07:43

【GridMask】《GridMask Data Augmentation》

arXiv-2020文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4GridMask5Experiments5.1ImageClassification5.2ObjectDetectiononCOCODataset5.3SemanticSegmentationonCityscapes5.4ExpandGridasRe
bryant_meng·2022-11-23 00:53

【Randaugment】《Randaugment：Practical automated data augmentation with a reduced search space》

Contributions4Method4.1Systematicfailuresofaseparateproxytask4.2Automateddataaugmentationwithoutaproxytask5Experiments5.1CIFAR
bryant_meng·2022-11-23 00:18

PIX2SEQ: A LANGUAGE MODELING FRAMEWORK FOR OBJECT DETECTION

2.1SEQUENCECONSTRUCTIONFROMOBJECTDESCRIPTIONS2.2ARCHITECTURE,OBJECTIVEANDINFERENCE2.3SEQUENCEAUGMENTATIONTOINTEGRATETASKPRIORS3EXPERIMENTS3.1EXPERIMENTALSETUP3.2MAIN
ZZE15832206526·2022-11-22 20:46

【多目标跟踪论文阅读笔记——FairMOT】

UnfairnessIssuesinOne-shotTrackers2.1Anchor机制2.2特征图2.3特征图尺寸3.FairMOT3.1Backbone3.2Multi-TaskLearning3.3Association4.Experiments4.1Visualization4.2Run-time4.3Com
书玮嘎·2022-11-22 08:17

【全文翻译】Can You Really Backdoor Federated Learning?

1Introduction2BackdoorAttackScenario3ModelUpdatePoisoningAttacks4Defenses5Experiments6Discussion摘要–联邦学习的分散性质使检测和防御对抗攻击成为一项艰巨的任务
白菜苗·2022-11-22 00:22

本周的总结

目录本周完成的计划论文阅读Abstract(摘要)1.Introduction（绪论）2.Approach（方法）3.Discussions（讨论）4.Experiments（实验）4.1.Setup（
ZN_daydayup·2022-11-22 00:41

＜＜多模态预训练—泛读＞＞2022：mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connec

Skip-connection三、mPLUG3.1、ModelArchitecture3.2、Cross-modalSkip-connectedNetwork3.3、Pre-trainingTasks四、Experiments
金克丝、·2022-11-20 01:46
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