Experiments】第6页

【SB-ReID】《Bag of Tricks and A Strong Baseline for Deep Person Re-identification》

Contributions3StandardBaseline4Method4.1WarmupLearningRate4.2RandomErasingAugmentation4.3LabelSmoothing4.4LastStride4.5BNNeck4.6CenterLoss5Experiments4

bryant_meng·2021-02-01 10:38

【Sparse R-CNN】《Sparse R-CNN：End-to-End Object Detection with Learnable Proposals》

arXiv-2020作者的博客：SparseR-CNN文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method5Experiments6Conclusion

bryant_meng·2021-01-20 10:56

通过实例深入理解sync.Map的工作原理

一.原生map的“先天不足”对于已经初始化了的原生map，我们可以尽情地对其进行并发读：//github.com/bigwhite/experiments/inside-syncmap/concur

Tony Bai·2020-10-10 12:00

Pysot训练过程整理（详细注释） - SiamRPN++ & ResNet50

rank,world_size=dist_init()#world_size：进程数量/任务数量/GPU数量#rank：进程ID#加载参数：合并args参数表（包含代码中定义参数以及experiments

沉小咚·2020-09-23 15:10

Voice Conversion by Cascading Automatic Speech Recognition and Text-to-Speech Synthesis with Prosody

&中科大文章目录abstractintroduction2.background3.proposedmethod3.1ASRengine3.2TTSmodel3.3.Prosodytransfer4.Experiments4.1

林林宋·2020-09-13 12:35

（RefineDet）Single-Shot Refinement Neural Network for Object Detection论文阅读笔记

Single-ShotRefinementNeuralNetworkforObjectDetection论文阅读笔记2018Abstract1.Introduction2.RelatedWork3.NetworkArchitecture4.TrainingandInference5.Experiments5.1

AndyLiu1997·2020-09-13 06:01

Html界面弹出层实现方式

方式一：@Html.Partial（）调用“modalfade”类选择样品新增样品@Html.Partial("~/Views/Experiments/Task/_SampleSelect.cshtml

muhuozhuyun·2020-09-13 05:55

C#：设置CefSharp的一些参数，比如忽略安全证书

------------吾亦无他,唯手熟尔，谦卑若愚，好学若饥-------------本次记录如何设置CefSharp忽略安全证书，以及他的一些其他配置参考网址：https://peter.sh/experiments

Qgee2013·2020-09-12 10:02

【多方向文字检测】《efficient scene text detection with textual attention tower》

（CCFB类）会议目录Abstract2.PROPOSEDMETHOD2.1ArchitectureOverview2.2.TextualAttentionTower2.3Lossfunction3.Experiments3.1BenchmarkDatasetsandData

猫猫与橙子·2020-09-11 22:21

Network-in-Network论文阅读笔记

ConvolutionalNeuralNetworks3.NetworkInNetwork3.1MLPConvolutionLayers3.2GlobalAveragePooling3.3NetworkInNetworkStructure4Experiments5Conclusions

comic97·2020-09-11 21:09

cc:184 Key generator/g_d1_bn/beta not found in checkpoint

目前我正在執行github上的專案pcgreat/zi2zi的專案執行過程中發生錯誤log如下這是我的test.sh文件PYTHONPATH=.pythoninfer.py--model_dir=experiments

Tzu-Heng·2020-09-10 20:01

cat

software.intel.com/content/www/us/en/develop/articles/cache-allocation-technology-telco-nfv-noisy-neighbor-experiments.html

大a艺术家·2020-08-27 17:07

（十五）论文阅读 | 目标检测之DR Loss

Introduction2.RelatedWork3.DRLoss3.1Ranking3.2DistributionalRanking3.3RecoverClassificationfromRanking4.Experiments4.1ParametersinDRLoss4.2EffectofParameters4.3ComparisonwithState-of

Skies_·2020-08-26 12:41

（十一）论文阅读 | 视觉关系检测

Skies_·2020-08-26 12:09

webrtc中的rtp扩展 rtp-hdrext

在代码中，可以直接搜索：structRTPHeaderExtension；https://webrtc.org/experiments/rtp-hdrext/HomeExperimentsRtphdrextrtp-hdrextShowContentsUnderneaththispage

chinabinlang·2020-08-25 17:42

论文笔记：mixup: BEYOND EMPIRICAL RISK MINIMIZATION

Experiments一些数据集的classificationMemorizationofcorruptedlabelsRobustnesstoadversarialexamplesStabilizationofGANsAblationstudies

weixin_39901859·2020-08-24 04:06

Removing Propagation Redundant Constraints in Redundant Modeling 翻译（二）& 全文总结

6.EXPERIMENTS我们可以利用传播冗余的推理来消除传播冗余。然后我们得到一个传播强度完全相同但传播器更少的模型。这可以转化为更快的传播。

达小七·2020-08-24 03:47

（DenseNet）Densely Connected Convolutional Networks论文阅读笔记

DenseNet）DenselyConnectedConvolutionalNetworks论文阅读笔记2018Abstract1.Introduction2.RelatedWork3.DenseNets4.Experiments4.1Datasets4.2Training4.3ClassificationResultsonCIFARandSVHN4.4ClassificationRes

AndyLiu1997·2020-08-23 03:51

在MQTT中使用SSL/TLS提高安全性

翻译自：http://rockingdlabs.dunmire.org/exercises-experiments/ssl-client-certs-to-secure-mqtt在MQTT中使用SSL/

moxiaomomo·2020-08-23 00:50

论文阅读笔记（2）——Bidirectional LSTM-CRF Models for Sequence Tagging（用于序列标记的双向LSTM-CRF模型）

Models2.1LSTMNetworks2.2BidirectionalLSTMNetworks2.3CRFnetworks2.4LSTM-CRFnetworks2.5BI-LSTM-CRFnetworks3.Trainingprocedure4.Experiments4.1Data4.2Features4.2.1Spellingfeatures

StriveQueen·2020-08-22 19:56

[CVPR2020] AdderNet阅读笔记

文章目录1Introduction2Methods2.1AdderNetworks2.2梯度回传2.3自适应的学习率缩放3Experiments4Q&AAdderNet是北大和华为诺亚方舟实验室共同完成的一篇文章

RainbowSun1102·2020-08-22 14:32

TensorFlow——Fashion mnist示例

/experiments/","num_workers":8,"train_batch_size":64,"test_batch_size":128,"prefecth_times":1,"max_epochs

扎手的苍耳·2020-08-22 12:56

selenium add_argument 常用参数表收集

seleniumadd_argument参数表https://peter.sh/experiments/chromium-command-line-switches/chrome_options.add_argument

清风冷吟·2020-08-22 04:57

selenium add_argument 常用参数表收集

https://peter.sh/experiments/chromium-command-line-switches/chrome_options.add_argument('--user-agent

nofuck~·2020-08-22 04:06

faster rcnn文件夹说明

fasterrcnn根目录下1、caffe-fast-rcnn文件夹这是caffe框架目录2、data文件夹用来存放pretrained模型，比如imagenet上的，以及读取文件的cache缓存3、experiments

qq小小布丁·2020-08-22 03:37

ECCV2020 | 论文阅读——CPNDet:Corner Proposal Network for Anchor-free, Two-stage Object Detection

CPNDet1Introduction2Approach2.1CPN网络框架2.2Inference阶段3Experiments4Conclusion论文地址：https://arxiv.org/abs

Liaojiajia2019·2020-08-22 02:16

ECCV2020 | 论文阅读——HoughNet: Integrating near and long-range evidence for bottom-up object detection

HoughNet1Introduction2Approach2.1Thelog-polar“votefield”2.2Votingmodule2.3Networkarchitecture3Experiments4Conclusion

Liaojiajia2019·2020-08-22 02:16

【论文笔记】Bayesian Loss for Crowd Count Estimation with Point Supervision

TheProposedMethod3.1.BackgroundandMotivation3.2.BayesianLoss3.3.BackgroundPixelModelling3.4.VisualizationandAnalysis4.Experiments4.1

Tra_cy·2020-08-22 01:08

YOLOv4: Optimal Speed and Accuracy of Object Detection-论文阅读（2）

YOLOv4:OptimalSpeedandAccuracyofObjectDetectionAbstract1.Introduction2.Relatedwork3.Methodology4.Experiments5

H速写不读书H·2020-08-22 00:41

论文阅读——MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Abstract1、Introduction2、PriorWork3、MobileNetArchitecture3.1、深度可分离卷积3.2、网络结构和训练3.3、宽度乘子：更窄的模型3.4、分辨率乘子：减少表达4、Experiments4.1

雨•人·2020-08-22 00:39

论文阅读——YOLOv4:Optimal Speed and Accuracy of Object Detection

BagofFreebies（赠品包）2.3、Bagofspecials（特价包）3、Methodology3.1、结构选择3.2、BoF和BoS的选择3.3、额外提升3.4、YOLOv4的组成和细节4、Experiments4.1

雨•人·2020-08-22 00:06

论文阅读——Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

雨•人·2020-08-22 00:06

论文阅读——Deep Residual Learning for Image Recognition

目录前言Abstract1.Introduction2、RelatedWork3、DeepResidualLearning3.1、残差学习3.2、快捷恒等映射3.3、网络结构3.4、实现4、Experiments4.1

雨•人·2020-08-22 00:06

R实例：limma包分析Agilent 4x44K Arrays

数据获取：http://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-33005.研究内容：Effectsofcornoilgavageongeneexpressionprofiles

jlyq617·2020-08-21 13:05

【YOLO学习笔记】之YOLO v1 论文笔记2（超详细：翻译+理解）

目录前言一、ComparisontoOtherDetectionSystems（与其他检测系统的比较）二、Experiments（实验）1、ComparisontoOtherReal-TimeSystems

水亦心·2020-08-21 05:38

十天内掌握线性代数：惊人的超速学习实验

94114/329073)原文链接:http://calnewport.com/blog/2012/10/26/mastering-linear-algebra-in-10-days-astounding-experiments-in-ultra-learning

samurai·2020-08-20 22:39

Fast R-CNN roidb数据准备

/experiments/scripts/fast_rcnn.sh0VGG_CNN_M_1024pascal_voc--setEXP_DIRfoobarRNG_SEED42TRAIN.S

yang_502·2020-08-18 18:38

GhostNet: More Features from Cheap Operations论文初读

ModelCompression（二）CompactModelDesign四、Approach（一）GhostModuleforMoreFeatures（二）BuildingEfficientCNNs五、Experiments

不知道叫啥+1·2020-08-17 14:23

【PolyTransform】《PolyTransform：Deep Polygon Transformer for Instance Segmentation》

Contributions4Method4.1InstanceInitialization4.2FeatureExtractionNetwork4.3DeformingNetwork4.4PolygonTransformingLoss5Experiments5.1Dataset

bryant_meng·2020-08-17 12:29

【NasNet】《Learning Transferable Architectures for Scalable Image Recognition》

CVPR-2018文章目录1BackgroundandMotivation2Advantages/Contributions3Method4Experiments4.1Datasets4.2CIFAR-

bryant_meng·2020-08-17 08:51

百度飞桨PaddlePaddle论文复现训练营——论文阅读笔记：U-GAT-IT

文章目录一、写在前面二、论文背景三、论文阅读笔记1.Introduction2.Model2.1生成器GENERATOR2.2判别器DISCRIMINATOR2.3损失函数LOSSFUNCTION3.EXPERIMENTS

AItrust·2020-08-17 02:06

Linux环境下通过GDB调试C项目实战

通过GDB调试找到程序的bug请查看位于https://github.com/xmu-Linux101/Linux101/tree/201720182/experiments/gcc-5-gdb的代码这个是向量加法的程序

菱形继承·2020-08-10 13:17

Linux011 Sra toolkit安装及使用

根据SRA数据产生的特点，将SRA数据分为四类：Studies--研究课题Experiments--实验设计Runs--测序结果

caoqiansheng·2020-08-09 00:43

论文阅读：Spatial Transformer Networks

：SpatialTransformerNetworks（1）Author（2）Abstract（3）Conclusion（4）Introduction（5）SpatialTransformers（6）Experiments

Friedrich Yuan·2020-08-04 21:24

Fasttext

目录《BagofTricksforEfficientTextClassification》1、论文总览Abstract1.1Introduction1.2Modelarchitecture1.3Experiments1.4Discussionandconclusion2

努力努力努力努力·2020-08-03 22:54

深度学习笔记（十）---RNN时间序列详解

Abstract）：2.网络结构(Method)2.1RNN2.2RNN的变体2.2.1双向RNN2.2.2深层双向RNN2.3LSTM2.3.1LSTM内部结构详解2.4GRU3.实验分析以及代码实现(Experiments

Jayden yang·2020-08-03 03:11

CVPR 2020——Unsupervised Learning of Intrinsic Structural Representation Points

Abstract（二）Introduction（三）Method3.1.NetworkArchitecture3.2.ReconstructionLoss3.3.Cross-ObjectConsistency（四）Experiments4.1

Dujing2019·2020-08-02 15:10

ICRA 2020——Dilated Point Convolutions: On the Receptive Field Size of Point Convolutions on 3D Point

OntheReceptiveFieldSizeofPointConvolutionson3DPointCloudsAbstract（一）Introduction（二）RelatedWork（三）Approach（四）Experiments

Dujing2019·2020-08-02 15:09

显著性检测——GR模型

GR模型1.Introduction2.SaliencyModel2.1InitialSaliencyMap2.2SaliencyMapRefiningWithGraphRegularization3.Experiments4

JERRY6066·2020-08-02 13:12

CVPR2020 | 论文阅读——Dynamic Refinement Network for Oriented and Densely Packed Object Detection

DRNAbstract1Introduction2RelatedWork3Method3.1NetworkArchitecture3.2FeatureSelectionModule3.3DynamicRefinementHead3.4SKU110K-RDataset4Experiments4.1ExperimentalResults4.2AblationStudy5Conclusion

Liaojiajia2019·2020-08-02 13:20

推荐频道

Experiments】

【SB-ReID】《Bag of Tricks and A Strong Baseline for Deep Person Re-identification》

【Sparse R-CNN】《Sparse R-CNN：End-to-End Object Detection with Learnable Proposals》

通过实例深入理解sync.Map的工作原理

Pysot训练过程整理（详细注释） - SiamRPN++ & ResNet50

Voice Conversion by Cascading Automatic Speech Recognition and Text-to-Speech Synthesis with Prosody

（RefineDet）Single-Shot Refinement Neural Network for Object Detection论文阅读笔记

Html界面弹出层实现方式

C#：设置CefSharp的一些参数，比如忽略安全证书

【多方向文字检测】《efficient scene text detection with textual attention tower》

Network-in-Network论文阅读笔记

cc:184 Key generator/g_d1_bn/beta not found in checkpoint

cat

（十五）论文阅读 | 目标检测之DR Loss

（十一）论文阅读 | 视觉关系检测

webrtc中的rtp扩展 rtp-hdrext

论文笔记：mixup: BEYOND EMPIRICAL RISK MINIMIZATION

Removing Propagation Redundant Constraints in Redundant Modeling 翻译（二）& 全文总结

（DenseNet）Densely Connected Convolutional Networks论文阅读笔记

在MQTT中使用SSL/TLS提高安全性

论文阅读笔记（2）——Bidirectional LSTM-CRF Models for Sequence Tagging（用于序列标记的双向LSTM-CRF模型）

[CVPR2020] AdderNet阅读笔记

TensorFlow——Fashion mnist示例

selenium add_argument 常用参数表收集

selenium add_argument 常用参数表收集

faster rcnn文件夹说明

ECCV2020 | 论文阅读——CPNDet:Corner Proposal Network for Anchor-free, Two-stage Object Detection

ECCV2020 | 论文阅读——HoughNet: Integrating near and long-range evidence for bottom-up object detection

【论文笔记】Bayesian Loss for Crowd Count Estimation with Point Supervision

YOLOv4: Optimal Speed and Accuracy of Object Detection-论文阅读（2）

论文阅读——MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

论文阅读——YOLOv4:Optimal Speed and Accuracy of Object Detection

论文阅读——Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

论文阅读——Deep Residual Learning for Image Recognition

R实例：limma包分析Agilent 4x44K Arrays

【YOLO学习笔记】之YOLO v1 论文笔记2（超详细：翻译+理解）

十天内掌握线性代数：惊人的超速学习实验

Fast R-CNN roidb数据准备

GhostNet: More Features from Cheap Operations论文初读

【PolyTransform】《PolyTransform：Deep Polygon Transformer for Instance Segmentation》

【NasNet】《Learning Transferable Architectures for Scalable Image Recognition》

百度飞桨PaddlePaddle论文复现训练营——论文阅读笔记：U-GAT-IT

Linux环境下通过GDB调试C项目实战

Linux011 Sra toolkit安装及使用

论文阅读：Spatial Transformer Networks

Fasttext

深度学习笔记（十）---RNN时间序列详解

CVPR 2020——Unsupervised Learning of Intrinsic Structural Representation Points

ICRA 2020——Dilated Point Convolutions: On the Receptive Field Size of Point Convolutions on 3D Point

显著性检测——GR模型

CVPR2020 | 论文阅读——Dynamic Refinement Network for Oriented and Densely Packed Object Detection