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Wiley电子期刊(62)
SpringerLink电子期刊(2391)
NATURE电子期刊(11)
Elsevier电子期刊(2278)
Springer电子图书(43)
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ACS电子期刊(126)
在“
Elsevier电子期刊
”中,
命中:
2,278
条,耗时:0.0339901 秒
在所有数据库中总计命中:
5,014
条
1.
Concatenated spatially-localized
random
forest
s for hippocampus labeling in adult and infant MR brain images
作者:
Lichi Zhang
a
;
b
;
lichizhang@sjtu.edu.cn
Author Vitae
;
Qian Wang
a
;
wang.qian@sjtu.edu.cn
Author Vitae
;
Yaozong Gao
b
;
c
;
yzgao@cs.unc.edu
Author Vitae
;
Hongxin Li
e
;
lhx3129@163.com
Author Vitae
;
Guorong Wu
b
;
grwu@med.unc.edu
Author Vitae
;
Dinggang Shen
b
;
d
;
dgshen@med.unc.edu
Author Vitae
关键词:
Image segmentation
;
Random
forest
;
Brain MR images
;
Atlas selection
;
Clustering
刊名:Neurocomputing
出版年:2017
2.
A genetic algorithm approach to optimising
random
forest
s applied to class engineered data
作者:
Eyad Elyan
;
e.elyan@rgu.ac.uk
;
Mohamed Medhat Gaber
m.gaber1@rgu.ac.uk
关键词:
Random
forest
s
;
Genetic algorithm
;
Class decomposition
;
Life science
刊名:Information Sciences
出版年:2017
3.
Field evaluation of a
random
forest
activity classifier for wrist-worn accelerometer data
作者:
Toby G. Pavey
a
;
b
;
toby.pavey@qut.edu.au
;
Nicholas D. Gilson
b
;
Sjaan R. Gomersall
b
;
Bronwyn Clark
c
;
Stewart G. Trost
a
关键词:
Accelerometer
;
Random
forest
classifier
;
Physical activity
;
Wrist
刊名:Journal of Science and Medicine in Sport
出版年:2017
4.
Exposure assessment models for elemental components of particulate matter in an urban environment: A comparison of regression and
random
forest
approaches
作者:
Cole Brokamp
a
;
b
;
cole.brokamp@cchmc.org
;
Roman Jandarov
b
;
M.B. Rao
b
;
Grace LeMasters
b
;
c
;
Patrick Ryan
a
;
b
关键词:
Elemental PM2.5
;
Land use regression
;
Random
forest
刊名:Atmospheric Environment
出版年:2017
5.
Growing
random
forest
on deep convolutional neural networks for scene categorization
作者:
Shuang Bai
shuangb@bjtu.edu.cn
关键词:
Scene categorization
;
Random
forest
;
Convolutional neural networks
;
Feature selection
刊名:Expert Systems with Applications
出版年:2017
6.
Estimating grassland LAI using the
Random
Forest
s approach and Landsat imagery in the meadow steppe of Hulunber, China
作者:
Zhen-wang LI
;
lizhenwang@126.com
;
Xiao-ping XIN
;
Huan TANG
;
Fan YANG
;
Bao-rui CHEN
;
Bao-hui ZHANG
;
zhangbaohui@caas.cn
关键词:
leaf area index
;
Random
Forest
s grassland
;
remote sensing
;
Hulunber
刊名:Journal of Integrative Agriculture
出版年:2017
7.
Real-time contrasts control chart using
random
forest
s with weighted voting
作者:
Seongwon Jang
1
;
jsw900806@korea.ac.kr
;
Seung Hwan Park
1
;
udongpang@korea.ac.kr
;
Jun-Geol Baek
;
jungeol@korea.ac.kr
关键词:
Real-time contrasts (RTC)
;
Fault detection
;
Fault isolation
;
Random
forest
s
;
Weighted voting
;
Class imbalance
刊名:Expert Systems with Applications
出版年:2017
8.
Comparison of object-based and pixel-based
Random
Forest
algorithm for wetland vegetation mapping using high spatial resolution GF-1 and SAR data
作者:
Bolin Fu
a
;
b
;
c
;
Yeqiao Wang
c
;
Anthony Campbell
c
;
Ying Li
a
;
liying_neigae@126.com
;
Bai Zhang
a
;
Shubai Yin
d
;
Zefeng Xing
a
;
b
;
Xiaomin Jin
a
;
b
关键词:
Wetland vegetation mapping
;
Image fusion
;
Random
Forest
classifier
;
GF-1
;
SAR
;
Northeast China
刊名:Ecological Indicators
出版年:2017
9.
Deep neural networks, gradient-boosted trees,
random
forest
s: Statistical arbitrage on the S&P 500
作者:
Christopher Krauss
;
a
;
christopher.krauss@fau.de
;
Xuan Anh Do
a
;
anh.do@fau.de
;
Nicolas Huck
b
;
nicolas.huck@icn-groupe.fr
关键词:
Finance
;
Deep learning
;
Gradient-boosting
;
Random
forest
s
;
Ensemble learning
刊名:European Journal of Operational Research
出版年:2017
10.
Permeability determination of cores based on their apparent attributes in the Persian Gulf region using Navie Bayesian and
Random
forest
algorithms
作者:
Pouria Behnoud far
a
;
P.Behnoud@aut.ac.ir
;
Pantea Hosseini
b
;
Ali Azizi
a
关键词:
Persian Gulf
;
Permeability
;
Archie's classification
;
Navie Bayesian algorithm
;
Random
forest
algorithm
;
Apparent attributes
刊名:Journal of Natural Gas Science and Engineering
出版年:2017
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