原创 Class4-Week2 Case study
文章目錄Classic NetworksLeNet-5AlexNetVGG-16Residual NetworksThe Problem of Deep Neural NetworksArchitectureWhy ResNets
原创 Class1-Week2-Neural Networks Basics
文章目錄@[toc]Logistic RegressionDescriptionExample: Cat vs No-catLogistic FunctionLogistic Cost FunctionLoss(error) Fu
原创 Class1-Week4-Deep Neural Network
文章目錄Compute ProcessForward PropagationBackward PropagationMatrix DimensionsParameters vs HyperparametersDefinationT
原创 HUST-納米技術與應用結構課目錄
文章目錄概論......1納米技術的主要內容......1納米材料納米動力學納米生物學和納米藥物學納米電子學基本定義......2納米的定義納米科技發展的意義自然界的納米結構......3發展歷史......3人造納米材料與結構.
原创 Class3-Week1 ML Strategy1
文章目錄OrthogonalizationChain of assumptions in MLSetting up your GoalPrecision and RecallSingle Number Evaluation Met
原创 Class4-Week4 Face Recognition & Neural Style Transfer
文章目錄Face RecognitionFace Verification vs. Face RecognitionSiamese NetworkTriplet LossFace Verification and Binary c
原创 HUST-新能源技術PPT目錄
文章目錄緒論-能量與物質能量...1能量的分類與評級...4能量與人類文明...5能源資源生產與消費...6能源與環境...8能源的可持續發展...19海洋能潮汐能...21波浪能...24溫差能...25鹽差能...25海流能.
原创 Multi-Label Image Recognition with Graph Convolutional Networks(CVPR 2019)
Multi-Label Image Recognition with Graph Convolutional Networks Paper PDF 文章目錄IntorductionInnovationMethodGraph Con
原创 Class4-Week3 Object Detection
文章目錄Object LocalizationLandmarks detectionObject DetectionSliding Window DetectionConvolutional Implementation of S
原创 Image Classification vs. Object Detection vs. Image Segmentation
文章目錄Image ClassificationMulti-label ClassificationObject DetectionObject SegmentationIn Short 在計算機視覺領域,我們大多數人最常見的疑問
原创 Class4-Week1 Convolutional Neural Networks
文章目錄Why Padding?Why Pooling Layer?Why Convolutions? Why Padding? The main benefits of padding are the following:
原创 CNN-RNN: A Unified Framework for Multi-label Image Classification(CVPR 2016)
CNN-RNN: A Unified Framework for Multi-label Image Classification Paper PDF 文章目錄IntroductionInnovationMethodModelTr
原创 DeepFakes Datasets(2020.06)
Datasets URL Real Fake Audio Actor Visual Quality(SSIM) Method Release Date Info UADFV URL 49 49 no - 0.82 D
原创 Learning Generalized Spoof Cues for Face Anti-spoofing
Learning Generalized Spoof Cues for Face Anti-spoofing paper PDF 文章目錄IntorductionInnovationMethodAnomaly detectionR
原创 Seeing Voices and Hearing Faces: Cross-modal biometric matching(CVPR 2018)
Seeing Voices and Hearing Faces: Cross-modal biometric matching Paper PDF 文章目錄IntroductionInnovationMethodCross-Mod