advantages

Some Technical Advantages about Belt Conveyor

Withtheadvantagesoflargeconveyingcapacity,simplestructure,easymaintenanceandstandardizedparts.Beltconveyoriswidelyusedtoconveytheincompactmaterialsandendarticlesinmining,metallurgy,andcoalindustry,etc
cnm2386·2024-09-07 08:19

【PSA】《Polarized Self-Attention: Towards High-quality Pixel-wise Regression》

arXiv-2020文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method5Experiments5.1DatasetsandMetrics5.2PSAvs.Baselines5.3SemanticSegmentation5.4AblationStudy6Conclusion
bryant_meng·2024-02-05 17:24

ChatGPT在医学中的应用概述：应用、优势、局限性、未来前景和伦理思辨

FrontiersinArtificialIntelligence发表一篇ChatGPT的文献综述的文章，题目是《ChatGPTinmedicine:anoverviewofitsapplications,advantages
AI明说·2024-01-20 21:09

QCN9024: The future of wireless communications, five major advantages over competitors

Intoday'srapidlydevelopingfieldofwirelesscommunications,chipperformanceandfunctionalityarecrucial.QCN9024,awirelesscommunicationchipdevelopedbyQualcomm,hasbecomeamarketleaderwithitsexcellentperformanc
Wallytech·2024-01-19 09:54

【GAM】《Global Attention Mechanism：Retain Information to Enhance Channel-Spatial Interactions》

arXiv-2021文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method5Experiments5.1DatasetsandMetrics5.2ClassificationonCIFAR
bryant_meng·2024-01-15 00:38

【NL】《Non-local Neural Networks》

CVPR-2018文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Non-localNeuralNetworks4.1Formulation4.2Instantiations4.3NonlocalBlock4.4VideoClassificationModels5Experiments5.1Datasets5.2E
bryant_meng·2024-01-15 00:36

【CCNet】《CCNet：Criss-Cross Attention for Semantic Segmentation》

ICCV-2019文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method5Experiments5.1DatasetsandMetrics5.2ExperimentsonCityscapess5.3ExperimentsonADE20K5.4ExperimentsonCOCO6Conclusion
bryant_meng·2024-01-15 00:35

【Shuffle Attention】《SA-Net：Shuffle Attention for Deep Convolutional Neural Networks》

ICASSP-2021文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method5Experiments5.1DatasetsandMetrics5.2ClassificationonImageNet
bryant_meng·2023-12-22 18:06

【NAM】《NAM：Normalization-based Attention Module》

NeurIPS-2021workshop文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method5Experiments5.1DatasetsandMetrics5.2Experiments6Conclusion
bryant_meng·2023-12-22 18:03

【Yolov5 Traffic Sign】《Improved YOLOv5 network for real-time multi-scale traffic sign detection》

NeuralComputingandApplications2023文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method4.1TheimprovedYOLOv5snetworkframework4.2AF-FPNstructure4.3Dataaugmentation5Experiments5.1Datas
bryant_meng·2023-12-03 09:15

【EMFace】《EMface: Detecting Hard Faces by Exploring Receptive Field Pyramids》

arXiv-2021文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method5Experiments5.1DatasetsandMetrics5.2AblationStudy5.3ComparisonwithState-of-the-Arts6Conclusion
bryant_meng·2023-11-28 08:41

Writing Day 7 IELTS gu_writing

WritingDay720190314gu_writing全文翻译2：老龄化社会+观点类题目（advantages/disadvantages）题型写作要点+段落的数目题目：Inmanycountry,
米妮爱分享·2023-09-29 02:14

What are the advantages of pipes over temporary files?

Pipesandtemporaryfilesbothserveasameansofinter-processcommunication(IPC)ordatastorage,buttheyhavedifferentcharacteristicsandadvantages.Herearesomereasonswhypipesmightbepreferredovertemporaryfiles:Spee
青衫客36·2023-09-22 06:17

What are the advantages of using RPC?RPC是面向服务架构（SOA）的主要模式之一，它利用了网络技术、消息队列、序列化技术等多种组件实现分布式应用间的数据交换和通信

作者：禅与计算机程序设计艺术1.简介远程过程调用（RemoteProcedureCall，RPC）是一种分布式计算通信协议，用于在不同的机器上执行不同函数或方法，并且能够像本地方法一样方便地调用。RPC是面向服务架构（SOA）的主要模式之一，它利用了网络技术、消息队列、序列化技术等多种组件实现分布式应用间的数据交换和通信。在分布式系统中，通常存在着不同机器上的多个进程或线程需要相互通信和协作。为了
禅与计算机程序设计艺术·2023-08-29 20:37

WSL 配置 Oracle 19c 客户端

Documentation:https://help.ubuntu.com*Management:https://landscape.canonical.com*Support:https://ubuntu.com/advantageS
金桔数科·2023-08-23 13:26

【YOLOX】《YOLOX：Exceeding YOLO Series in 2021》

arXiv-2021文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method5Experiments5.1DatasetsandMetrics6Conclusion
bryant_meng·2023-08-10 16:58

【MegDet】《MegDet：A Large Mini-Batch Object Detector》

CVPR-2018文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method4.1LearningRateforLargeMini-Batch4.2Cross-GPUBatchNormalization5Experiments5.1Largemini-batchsize
bryant_meng·2023-07-28 00:18

【Soft NMS】《Soft-NMS – Improving Object Detection With One Line of Code》

ICCV-2017文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method5Experiments5.1Results5.2SensitivityAnalysis5.3WhendoesSoft-NMSworkbetter
bryant_meng·2023-07-24 20:08

【EfficientDet】《EfficientDet：Scalable and Efficient Object Detection》

CVPR-2020文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method4.1BiFPN4.2EfficientDet5Experiments5.1Datasets5.2EfficientDetforObjectDetection5.3EfficientDetforSemanticSegmentation5.4Ab
bryant_meng·2023-06-16 14:36

Model Checking(模型检测)

Advantages:(1)这是一个完全自动的过程，不需要测试有专业的数学方面的知识；（2）当设计
Tancenter·2023-06-16 05:15

How to Talk About Advantages in English

enamoredadjIfyouareenamoredofsomething,youlikeoradmireitalot.Ifyouarenotenamoredofsomething,youdislikeordisapproveofit.I'msoenamoredbyit.Ibecametotallyenamoredofthewildflowersthere.swingaroundIfsomeon
nafoahnaw·2023-04-17 07:13

【SPD-Conv】《No More Strided Convolutions or Pooling：A New CNN Building Block for Low-Resolution XXX》

ECML-PKDD2022TheEuropeanConferenceonMachineLearningandPrinciplesandPracticeofKnowledgeDiscoveryinDatabases文章目录1BackgroundandMotivation2RelatedWork3Advantages
bryant_meng·2023-04-08 01:28

【CityPersons】《CityPersons：A Diverse Dataset for Pedestrian Detection》

CVPR-2017文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Aconvnetforpedestriandetection5CityPersonsdataset5.1Boundingboxannotations5.2Statistics5.3Benchmarking5.4Baselineexperiments6
bryant_meng·2023-04-08 01:57

【CrowdHuman】《CrowdHuman：A Benchmark for Detecting Human in a Crowd》

arXiv-2018文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4CrowdHumanDataset4.1DataCollection4.2ImageAnnotation4.3DatasetStatistics5Experiments5.1DatasetsandMetrics5.2Detectionresults
bryant_meng·2023-04-08 01:25

advantages.of.travelling.by.train

今天看了一部下载到硬盘里很久没有看的电影，当时纯粹是因为名字看起来很有吸引力，而我对火车的钟爱也别具一格。或许是我阅历不够，加上电影观看的数量比较少，所以看了这部电影，对我的冲击，远远大于之前看过的任何一部电影，任何一部。本以为只是一个人在火车上遇到另一个人，然后倾听对方的故事，没想到讲故事的人是被另一个故事中的人所欺骗，然后故事中的人C讲述的故事中的D所欺骗，D又被E所欺骗，一环扣一环的精神分裂
关山楼不二·2023-03-09 19:21

The advantages and disadvantages of a new factory near your community

Iliveinaprimarilyagriculturalcommunity,andmostofthepopulationliveshandtomouth.Parentskeepchildrenhomefromschooltoworkinthefields.Ifthereisafloodoradrought,peoplestarve.Anewfactorywouldmeanregularmonth
造物家英语·2023-02-17 18:24

【Copy-Paste】《Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation》

CVPR-2021文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method5Experiments5.1Datasets5.2Copy-Pasteisrobusttotrainingconfigurations5.3Copy-Pastehelpsdata-efficiency5.4Copy-Pasteandself
bryant_meng·2023-02-02 11:52

【KAPAO】《Rethinking Keypoint Representations：Modeling Keypoints and Poses as Objects for XXX》

ModelingKeypointsandPosesasObjectsforMulti-PersonHumanPoseEstimation》ECCV-2022文章目录1BackgroundandMotivation2RelatedWork3Advantages
bryant_meng·2023-02-02 11:52

【WiderPerson】《WiderPerson：A Diverse Dataset for Dense Pedestrian Detection in the Wild》

TMM-2019文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4WiderPersonDatasetA.DataCollectionB.AnnotationToolC.ImageAnnotationD.DatasetStatisticE.Benchmarking5ProvidedBaselineMethodA.Im
bryant_meng·2023-02-02 11:50

【Mixed Pooling】《Mixed Pooling for Convolutional Neural Networks》

2014Internationalconferenceonroughsetsandknowledgetechnology文章目录1BackgroundandMotivation2ReviewofConvolutionalNeuralNetworks3Advantages
bryant_meng·2023-01-17 11:12

【Hide-and-Seek】《Hide-and-Seek: A Data Augmentation Technique for Weakly-Supervised Localization xxx》

ICCV-2017文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method5Experiments5.1DatasetsandMetrics5.2Weakly-supervisedobjectlocalization5.3Weakly-supervisedsemanticimagesegmentation5.4
bryant_meng·2023-01-12 07:14

【DeepPose】《DeepPose：Human Pose Estimation via Deep Neural Networks》

CVPR-2014用Deeplearning方法做HumanPoseEstimation的鼻祖文章目录1BackgroundandMotivation2Advantages/Contributions3Method3.1PoseEstimationasDNN-basedRegression3.2CascadeofPoseRegressors4Experiments4.1Datasets4.2Res
bryant_meng·2023-01-10 09:47

【Sparse-to-Dense】《Sparse-to-Dense：Depth Prediction from Sparse Depth Samples and a Single Image》

ICRA-2018文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method5Experiments5.1Datasets5.2RESULTS6Conclusion
bryant_meng·2022-12-31 16:20

【Inception-v4】《Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning》

-10【Keras-Inception-resnetv1】CIFAR-10【Keras-Inception-resnetv2】CIFAR-10文章目录1BackgroundandMotivation2Advantages3Innovations4Method4.1Inception-v44.2
bryant_meng·2022-12-24 16:19

神经网络深度学习论文阅读

Thisfigureshowsmyclassificationandsummaryofthesepapers.Myreadingnotesarebelow.Eachnotefollowingtheheadlineisdividedintoseveralparts,whicharethesummary,advantages
Niklauseik·2022-12-15 22:48

【Homography Estimation】《Deep Image Homography Estimation》

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

The Advantages of Reading Widely

Manypeopletendtoonlyreadonetypeofgenreofbookshoweveritisimportanttoreadmorewidelyanditisabsolutelyimperativetobeknowledgeableasyougrowolder.Aswebecomemoremature,weshouldprocessessufficientideastobeabl
wowojn·2022-12-11 23:49

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

ICCV-2017文章目录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

paper reading：《Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks》

NIPS2015论文链接：https://arxiv.org/pdf/1506.01497.pdf.文章目录1BackgroundandMotivation2RelatedWork3Advantages
小苑同学·2022-12-07 02:13

【Distilling】《Learning Efficient Object Detection Models with Knowledge Distillation》

NIPS-2017文章目录1BackgroundandMotivation2Advantages/Contributions3Method3.1KnowledgeDistillationforClassificationwithImbalancedClasses3.2KnowledgeDistillationforRegressionwithTeacherBounds3.3HintLearning
bryant_meng·2022-11-29 08:15

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

ICCV-2017【AITalking】FocalLossICCV2017现场演讲（Tsung-YiLin）文章目录1BackgroundandMotivation2Advantages/Contributions
bryant_meng·2022-11-25 11:27

【Sampling】《Prime Sample Attention in Object Detection》

原文地址：https://arxiv.org/abs/1904.04821文章目录1BackgroundandMotivation2Advantages3Contributions4Method4.1IoU-HLR4.2Score-HLR4.3Importance-basedSampleReweighting4.4
请痛捶我·2022-11-24 19:45

【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》

CVPRW-2020文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method4.1Systematicfailuresofaseparateproxytask4.2Automateddataaugmentationwithoutaproxytask5Experiments5.1CIFAR
bryant_meng·2022-11-23 00:18

【YOLOv2】《YOLO9000：Better, Faster, Stronger》

CVPR-2017部分整理参考YOLO：YOLOv1,YOLOv2,YOLOv3,TinyYOLO，YOLOv4,YOLOv5详解文章目录1BackgroundandMotivation2Advantages
bryant_meng·2022-11-19 02:34

【DropBlock】《DropBlock：A regularization method for convolutional networks》

NIPS-2018文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4DropBlock5Experiments5.1ImageNetClassification5.1.1DropBlockinResNet
bryant_meng·2022-11-17 09:53

【HRNet】《Deep High-Resolution Representation Learning for Human Pose Estimation》

https://github.com/leoxiaobin/deep-high-resolution-net.pytorch文章目录1BackgroundandMotivation2RelatedWork3Advantages
bryant_meng·2022-11-05 15:12

【MagNet】《Progressive Semantic Segmentation》

CVPR-2021文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4Method4.1Multistageprocessingpipeline4.2Refinementmodule4.3MagNetFast5Experiments5.1Datasets5.2ExperimentsontheCityscapesdata
bryant_meng·2022-10-27 11:52

【Stochastic Depth】《Deep Networks with Stochastic Depth》

ECCV-2016文章目录1BackgroundandMotivation2RelatedWork3Advantages/Contributions4DeepNetworkswithStochasticDepth5Experiments5.1Datasets5.2Results6Conclusion
bryant_meng·2022-10-21 07:37
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