regression model
2020.06.18 23:20
댓글 6
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WHRIA
2020.06.18 23:25
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WHRIA
2020.06.19 22:06
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WHRIA
2020.06.20 21:22
layer {
name: "pool5/7x7_s1"
type: "Pooling"
bottom: "conv5_3"
top: "pool5/7x7_s1"
pooling_param {
pool: AVE
kernel_size: 7
stride: 1
}
}
layer {
name: "whria_classifier"
type: "InnerProduct"
bottom: "pool5/7x7_s1"
top: "whria_classifier"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 1
weight_filler{
type: "gaussian"
std:0.01
}
bias_filler{
type:"constant"
value:0
}
}
}
layer {
bottom: "whria_classifier"
bottom: "label"
top: "loss"
type: "EuclideanLoss"
name: "loss"
} -
WHRIA
2020.06.20 21:24
layer {
name: "whria_classifier"
type: "InnerProduct"
bottom: "pool5/7x7_s1"
top: "whria_classifier"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 2
}
}
layer {
bottom: "whria_classifier"
bottom: "label"
top: "loss"
name: "loss"
type: "SoftmaxWithLoss"
}
layer {
name: "accuracy"
type: "Accuracy"
bottom: "whria_classifier"
bottom: "label"
top: "accuracy"
include {
phase: TEST
}
} -
WHRIA
2020.06.20 21:39
layer {
name: "pool5/7x7_s1"
type: "Pooling"
bottom: "conv5_3"
top: "pool5/7x7_s1"
pooling_param {
pool: AVE
kernel_size: 7
stride: 1
}
}
layer {
name: "whria_classifier1"
type: "InnerProduct"
bottom: "pool5/7x7_s1"
top: "whria_classifier1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 16
}
}
layer {
name: "relu_whria1"
type: "ReLU"
bottom:"whria_classifier1"
top: "whria_classifier1"
}
layer {
name : "drop16"
type : "Dropout"
bottom : "whria_classifier1"
top: "whria_classifier1"
dropout_param {
dropout_ratio:0.5
}
}
layer {
name:"whria_classifier2"
type: "InnerProduct"
bottom:"whria_classifier1"
top:"whria_classifier2"
inner_product_param{
num_output: 1
weight_filler{
type: "gaussian"
std:0.01
}
bias_filler{
type:"constant"
value:0
}
}
}
layer {
bottom: "whria_classifier2"
bottom: "label"
top: "loss"
type: "EuclideanLoss"
name: "loss"
} -
WHRIA
2020.06.20 22:12
layer {
name: "whria_classifier1"
type: "InnerProduct"
bottom: "pool5/7x7_s1"
top: "whria_classifier1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 32
}
}
layer {
name: "relu_whria1"
type: "ReLU"
bottom:"whria_classifier1"
top: "whria_classifier1"
}
layer {
name : "drop_whria1"
type : "Dropout"
bottom : "whria_classifier1"
top: "whria_classifier1"
dropout_param {
dropout_ratio:0.5
}
}
layer {
name: "whria_classifier2"
type: "InnerProduct"
bottom: "whria_classifier1"
top: "whria_classifier2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 32
}
}
layer {
name: "relu_whria2"
type: "ReLU"
bottom:"whria_classifier2"
top: "whria_classifier2"
}
layer {
name : "drop_whria2"
type : "Dropout"
bottom : "whria_classifier2"
top: "whria_classifier2"
dropout_param {
dropout_ratio:0.5
}
}
layer {
name:"whria_classifier_final"
type: "InnerProduct"
bottom:"whria_classifier2"
top:"whria_classifier_final"
inner_product_param{
num_output: 1
weight_filler{
type: "gaussian"
std:0.01
}
bias_filler{
type:"constant"
value:0
}
}
}
layer {
bottom: "whria_classifier_final"
bottom: "label"
top: "loss"
type: "EuclideanLoss"
name: "loss"
}
번호 | 제목 | 글쓴이 | 날짜 | 조회 수 |
---|---|---|---|---|
1819 | mAP 계산법 | WHRIA | 2019.02.24 | 45577 |
1818 | epitope spreading | han | 2006.05.09 | 41035 |
1817 | encfs | WHRIA | 2020.05.17 | 36033 |
1816 | Heinrich Law (1:29:300 Law) | WHRIA | 2007.08.12 | 25002 |
1815 | 일본 주소 [2] | WHRIA | 2008.06.28 | 24031 |
1814 | 사주팔자 프로그램 | 한승석 | 2003.02.16 | 20337 |
1813 | simple adblock | WHRIA | 2012.04.13 | 18121 |
1812 | 도란사민 | WHRIA | 2011.04.19 | 18115 |
1811 | 탤런트 이윤지씨와 함께 | WHRIA | 2010.02.04 | 17049 |
1810 | penicillin | han | 2003.12.10 | 15721 |
1809 | SSH tunnel | WHRIA | 2007.10.01 | 15090 |
1808 | geexbox [1] | han | 2006.12.01 | 14611 |
1807 | 아이피부과 개원 | WHRIA | 2010.01.18 | 14446 |
1806 | 세무회계 | WHRIA | 2010.01.31 | 14408 |
1805 | 증명사진 | WHRIA | 2010.03.14 | 14341 |
https://github.com/BVLC/caffe/issues/1396