Notice
Recent Posts
Recent Comments
Link
| 일 | 월 | 화 | 수 | 목 | 금 | 토 |
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |||
| 5 | 6 | 7 | 8 | 9 | 10 | 11 |
| 12 | 13 | 14 | 15 | 16 | 17 | 18 |
| 19 | 20 | 21 | 22 | 23 | 24 | 25 |
| 26 | 27 | 28 | 29 | 30 | 31 |
Tags
- Gilbert Strang
- 백준
- arm칩에안드로이드
- CNN구조정리
- ios원스토어
- adversarialattackonmonoculardepthestimation
- 선형대수학
- 아이폰원스토어
- CS231nAssignment1
- CS231n
- pycharmerror
- CS231nSVM
- monoculardepthestimation
- 백준알고리즘
- CS231ntwolayerneuralnet
- 선대
- 맥실리콘
- Linear algebra
- CNNarchitecture
- ㅐㅕ세ㅕㅅ
- BOJ
- gpumemory
- Algorithm
- CS231nAssignments
- RegionProposalNetworks
- MIT
- professor strang
- MacOS
- BAEKJOON
- 맥북원스토어
Archives
- Today
- Total
목록CNN구조정리 (1)
개발로 하는 개발
[CNN] architecture
CNN( = ConvNet) - sequence of layers - each layer of a ConvNet transforms one volue of activations to another through a differientable function - one volume of activations = activation map = feature map ReLU(nonlinear) layer : activates relevant responses Fully-Connected Layer : each neuron in a layer will be connected to all the numbers in the previous volume Pooling Layer : downsampling operat..
Study
2024. 2. 6. 17:26