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2017년 6월 23일 (금) 18:20 판 (원본 보기)
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2017년 6월 23일 (금) 18:20 판 (원본 보기)
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5번째 줄: 5번째 줄:
 
* https://www.quora.com/What-exactly-is-the-degradation-problem-that-Deep-Residual-Networks-try-to-alleviate
 
* https://www.quora.com/What-exactly-is-the-degradation-problem-that-Deep-Residual-Networks-try-to-alleviate
 
* dl with torch
 
* dl with torch
−
 
  
 
==[[Recommendation]]==
 
==[[Recommendation]]==

2017년 6월 23일 (금) 18:20 판

ril

  • https://medium.com/technologymadeeasy/the-best-explanation-of-convolutional-neural-networks-on-the-internet-fbb8b1ad5df8
  • http://nmhkahn.github.io/Casestudy-CNN
  • https://stats.stackexchange.com/questions/205150/how-do-bottleneck-architectures-work-in-neural-networks
  • https://www.quora.com/What-exactly-is-the-degradation-problem-that-Deep-Residual-Networks-try-to-alleviate
  • dl with torch

Recommendation

dl

  • CUDA기타설치
  • nets
    • dilated cnn
    • pathnet
    • ResNet
    • GoogLeNet (Inception)
  • Learning to learn by GD by GD
  • Face
  • Person re-identification
  • Generative Models
  • Batch Normalization
  • YOLO
  • Essential Cheat Sheets for Machine Learning and Deep Learning Engineers
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