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  • ResidualNet.pdf


    Deep Residual Learning for Image Recognition Kaim

    residual net works Image se Net set learning layers dee

    Sun Dec 08 14:33:17 CST 2019

    资源下载/ 深度学习
    10
  • 2017-07-31-ResNet论文翻译——中文版_.pdf


    SnailTyan ● 首页 ● 分类 ● 归档

    residual net works learning Net 翻译 论文 dee 作者 layers

    Wed Dec 11 11:48:21 CST 2019

    资源下载/ 深度学习
    11
  • UAV-6G-mobile edge.pdf


    IEEE INTERNET OF THINGS JOURNAL. 1 UAV Communicat

    wireless net works de UAV Member Senior IOT faced space-air-ground

    Wed Dec 11 11:31:27 CST 2019

    资源下载/ Xedge
    13
  • Notes on Convolutional Neural Networks.pdf


    Notes on Convolutional Neural Networks Jake Bouvr

    net neural derivation work convolutional works Convolutional descr 机器 extended

    Sun Dec 08 14:33:17 CST 2019

    资源下载/ rational rose
    10
  • A tutorial on training recurrent neural networks.pdf


    1 A tutorial on training recurrent neural netw

    revision net recurrent works neural training AIS tutorial EKF covering

    Sun Dec 08 14:33:17 CST 2019

    资源下载/ rational rose
    10
  • Modeling Information Diffusion in Online Social Networks with Partial Differential Equations.pdf


    ar X iv :1 31 0. 05 05 v1 [ cs .S I]

    social net online works information works. diffusion spreading ofinformation ism

    Sun Dec 08 14:33:17 CST 2019

    资源下载/ ansible
    10
  • hive调优.pdf


    Deep Dive content by Hortonworks, Inc. is licensed

    Hive •  ton Hor works Page Data content Inc.

    Sun Dec 08 14:33:17 CST 2019

    资源下载/ hive
    10
  • A Learning Algorithm for Boltzmann Machines.pdf


    COGNITIVE SCIENCE 9, 147-169 (1985) A Learning A

    connections net works con parallel massively University Department connectio 机器

    Sun Dec 08 14:33:17 CST 2019

    资源下载/ git/gitflow/gitlib
    10
  • gcForest.pdf


    Deep Forest: Towards An Alternative to Deep Neural

    gcForest net running dee neural works Nanjing contrast 机器 time

    Sun Dec 08 14:33:17 CST 2019

    资源下载/ C#/.net
    10
  • Densely Connected Convolutional Networks.pdf


    Densely Connected Convolutional Networks Gao Huan

    net layer layers Dense close convolutional works work subsequent 机器

    Sun Dec 08 14:33:17 CST 2019

    资源下载/ rational rose
    10
  • 1902.06720.pdf


    Wide Neural Networks of Any Depth Evolve as Linea

    net works neural wide work en training namics learning kernel.

    Sun Dec 08 14:33:17 CST 2019

    资源下载/ Xedge
    10
  • icml2016_tutorial_deep_residual_networks_kaiminghe.pdf


    error

    2016 icml works 学习 机器

    Sun Dec 08 14:33:17 CST 2019

    资源下载/ 虚拟开发vagrant
    10
  • fully_connected_netsfully_connected_nets


    ##################################################

    implement forward layer works net pass. 机器 approach modular return

    Sun Dec 08 14:33:17 CST 2019

    资源下载/ C#/.net
    10
  • 1511.06434.pdf


    Under review as a conference paper at ICLR 2016 U

    CNNs con learning. net works convolutional supervised learning deep Research

    Sun Dec 08 14:33:17 CST 2019

    资源下载/ C#/.net
    10
  • RPN.pdf


    1 Faster R-CNN: Towards Real-Time Object Detecti

    work net region Fast RPN object detection R-CNN works features

    Sun Dec 08 14:33:17 CST 2019

    资源下载/ ECN
    11
  • Which Deep Learning Framework is Growing Fastest.pdf


    Which Deep Learning Framework is Growing Fastest?

    Torch articles Py frame demand usage learningframe deep works TensorFlow

    Sun Dec 08 14:33:17 CST 2019

    资源下载/ Xedge
    11
  • 开源代码文献.doc


    人群分析  Deep Spatio-Temporal Residual Networks for

    https ​​ " Deep ​github.com​ Practices Good works wide-crowd-flows-prediction works-for-city

    Sun Dec 08 14:33:17 CST 2019

    资源下载/ 恶意代码防范
    11
  • deeplearn001.pdf


    Deep Forest: Towards an Alternative to Deep Neural

    gcForest dee neural net works performance hyper-parameter effort great re-quire

    Sun Dec 08 14:33:17 CST 2019

    资源下载/ netbeans
    11
  • Deep neural networks employing multi-task learning and stacked bottleneck features for speech synthesis.pdf


    DEEP NEURAL NETWORKS EMPLOYING MULTI-TASK LEARNING

    features synthe speech DNNs hidden complex stacked bottleneck learning works

    Sun Dec 08 14:33:17 CST 2019

    资源下载/ Xedge
    12
  • 14849-66902-1-PB.pdf


    When and Why Are Deep Networks Better than Shallow

    works Institute functions net function local Technology Claremont CA Mathe

    Sun Dec 08 14:33:17 CST 2019

    资源下载/ 策略引擎
    18
  • arduino/Arduino

  • arduino/arduino-cli

  • wuyouzhuguli/SpringAll

  • mongodb/node-mongodb-native

  • go-redis/redis

  • beamofsoul/BusinessInfrastructurePlatformGroupVersion

  • zhouzeqian/base

  • zeromq/jeromq

  • mkoppanen/php-zmq

  • erickt/rust-zmq

  • progrium/nullmq

  • 839536/kettle

  • suyaollyz/kettle-scheduler

  • magwyz/pastec

  • feiskyer/sdn-handbook

  • microsoft/SDN

  • hubo1016/vlcp

  • Cloudslab/cloudsimsdn

  • rancher/k3s

  • tektoncd/pipeline

  • ericchiang/k8s

  • open-cmdb/cmdb

  • pycontribs/jira

  • teamatldocker/jira

  • baidu/openedge

  • OpenNetworkingFoundation/5G-xHaul

  • herlesupreeth/OAI-5G

  • rebeccabernie/ResearchMethods-5G

  • esig/dss

  • 生成数字签名

  • EngineHub/CraftBook

  • philanc/plc

  • flosse/node-plc

  • yujunhao8831/spring-boot-start-current

  • sufuf3/ONOS_install_script

  • tzaeschke/tinspin-indexes

  • kzwang/elasticsearch-image

  • GSA/asis

  • hectorm/pzntg

  • emiliofidalgo/obindex

  • qq547276542/Agriculture_KnowledgeGraph

  • Alok991/Activity_brain_wave_prediction

  • mongolab/dex

  • servicemesher/istio-knowledge-map

  • feelschaotic/AndroidKnowledgeSystem

  • cglib/cglib

  • cesanta/mongoose-os

  • docs4dev/docs4dev

  • kubeedge/kubeedge

  • locationtech/geowave

  • zhonglinlin1305/spring-boot-sample

  • eclipse-iofog/iofog.org

  • FujiZ/ns-3

  • HKUST-SING/MQ-ECN-NS2

  • HKUST-SING/MQ-ECN-Software

  • sergiolucia/edgeAI

  • mbaddeley/usdn

  • mozilla-services/autograph

  • yinyanghu/RSA

  • devsecops/forecast

  • 自托管代理未显示在代理池下拉列表中

  • borismus/webvr-boilerplate

  • Vytek/VR-Awesome

  • LLK/scratch-flash

  • adamcohenrose/The-Eyes-Have-It

  • lots-of-things/quantum-comp

  • 从边缘节点推送kafka消息的最佳方法是什么?

  • 谷歌搜索正在恶化吗?衡量 2022 年 Google 的搜索质量

  • 诗经总览.一言以蔽之:龙马精神

  • 含糖饮料展开子菜单:运动饮料

  • 健康饮品-水

  • 元宇宙之“封号架构师眼中的元宇宙”

  • 机器学习十大算法-SVM支持向量机

  • 机器学习十大算法-贝叶斯bayes

  • 机器学习十大算法-随机森林

  • 机器学习十大算法-C4.5

  • 机器学习十大算法-Boosting

  • 机器学习十大算法-AdaBoost

  • 机器学习十大算法-分类回归树CART

  • 机器学习十大算法-SGD梯度下降

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