cslt Wiki - 用户贡献 [zh-cn]

Ling Luo 2015-12-07

2015-12-07T07:31:17Z

Luoling：/* Work last week */

== Work last week ==

1.technical report 90%

2.vihecle lane detection using OpenCV-Python

== Work this week ==

1.finish the technical report

2.normalization of the images so that the algorithm can be applied to different lighting conditions.

Ling Luo 2015-12-07

2015-12-07T07:26:40Z

Luoling：以“ == Work last week == 1.technical report 90% 2.vihecle lane detection using OpenCV-Python”为内容创建页面

== Work last week ==

1.technical report 90%

2.vihecle lane detection using OpenCV-Python

2015-12-7

2015-12-07T07:22:59Z

Luoling：

[[Dongxu Zhang 2015-12-7]]

[[Qixin Wang 2015-12-7]]

[[Yue Zhang 2015-12-7]]

[[Xiaoxi Wang 2015-12-7]]

[[Chao Xing 2015-12-7]]

[[Tianyi Luo 2015-12-7]]

[[Xiangyu Zeng 2015-12-7]]

[[Mengyuan Zhao 2015-12-07]]

[[Xuewei Zhang 2015-12-07]]

[[Lantian Li 2015-12-07]]

[[Zhiyuan Tang 2015-12-07]]

[[Zhiyong Zhang 2015-12-07]]

[[Ling Luo 2015-12-07]]

Ling Luo 2015-11-30

2015-12-02T09:15:45Z

Luoling：

Work Last Week

----
1.finished ner(named-entity-recognize) task(Java edition 1.6)

2.Technical report of the benchmark work(70%)

3.learning Python-OpenCV to detect lane marks.I found this method in stackoverflow quite helpful.
[http://stackoverflow.com/questions/26145806/filling-contours-in-opencv Filling Contours in OpenCV]

4*.A guide report for learning word2vec from the basic(maybe useful for newbees)(50%) while learning to use Latex

Ling Luo 2015-11-30

2015-12-02T09:13:20Z

Luoling：

Ling Luo 2015-11-30

2015-12-02T09:12:37Z

Luoling：

Ling Luo 2015-11-30

2015-12-02T09:11:21Z

Luoling：

Ling Luo 2015-11-30

2015-12-02T09:09:32Z

Luoling：以“ Work Last Week ---- 1.finished ner(named-entity-recognize) task(Java edition 1.6) 2.Technical report of the benchmark work(70%) 3.learning Python-OpenCV to det...”为内容创建页面

Work Last Week

----
1.finished ner(named-entity-recognize) task(Java edition 1.6)

2.Technical report of the benchmark work(70%)

3.learning Python-OpenCV to detect lane marks.I found this method in stackflow quite helpful.
[http://stackoverflow.com/questions/26145806/filling-contours-in-opencv 链接文字]

4*.A guide report for learning word2vec(maybe useful for newbees)(50%)

2015-11-30

2015-12-02T08:58:37Z

Luoling：

[[Mengyuan Zhao 2015-11-30]]

[[Tianyi Luo 2015-11-30]]

[[Qixin Wang 2015-11-30]]

[[Dongxu Zhang 2015-11-30]]

[[Chao Xing 2015-11-30]]

[[Yue Zhang 2015-11-30]]

[[Yazhou Gao 2015-11-30]]

[[Xiaoyue Gao 2015-11-30]]

[[Xiaoxi Wang 2015-11-30]]

[[Hui Tang 2015-11-30]]

[[Zhiyuan Tang 2015-11-30]]

[[Lantian Li 2015-11-30]]

[[Rong Liu 2015-11-30]]

[[Xuewei Zhang 2015-11-30]]

[[Xiangyu Zeng 2015-11-30]]

[[Ling Luo 2015-11-30]]

Asr-intern-week

2015-12-01T09:50:31Z

Luoling：/* Intern Working Timetable */

==Intern Working Timetable==

'X' absent
'O' present

{|class=wikitable
! !!周一 !! 周二 !! 周三 !! 周四 !! 周五 !! 周六 !! 周日
|-
|Dong Xu Zhang|| O ||O ||O ||?/O ||O/X ||O ||O
|-
| Yang Yu || O ||O ||O ||O ||O ||O ||O
|-
| Hui Tang || O ||O ||O ||O ||O ||O ||O
|-
| Qixin Wang || O ||X ||O ||X ||O ||O ||O
|-
| Xiangyu Zeng|| X ||X/O ||O ||O ||O ||O ||X
|-
| xiaoyue Gao|| 0 ||O ||O ||O ||O ||x ||X
|-
| peicheng Zhang|| x ||x ||x ||x ||0 ||x ||0
|-
| Yazhou Gao|| O ||O ||O ||O ||X ||X ||X
|-
| Haotian Shi|| X ||O ||O ||O ||X ||0 ||0
|-
| Ling Luo|| X ||O ||X ||O ||0 ||x ||0
|-
| Yue Zhang|| 0 ||O ||O ||O ||0 ||X ||X
|}

Asr-intern-week

2015-12-01T09:20:09Z

Luoling：/* Intern Working Timetable */

Status report

2015-09-27T10:56:20Z

Luoling：

[[2015-01-05]]

[[2015-01-12]]

[[2015-01-19]]

[[2015-01-26]]

[[2015-02-02]]

[[2015-02-09]]

[[2015-03-08]]

[[2015-03-15]]

[[2015-03-23]]

[[2015-03-30]]

[[2015-04-07]]

[[2015-04-13]]

[[2015-04-20]]

[[2015-04-27]]

[[2015-05-04]]

[[2015-05-11]]

[[2015-05-17]]

[[2015-05-24]]

[[2015-06-01]]

[[2015-06-08]]

[[2015-06-15]]

[[2015-06-29]]

[[2015-07-06]]

[[2015-07-13]]

[[2015-07-20]]

[[2015-07-27]]

[[2015-08-02]]

[[2015-08-10]]

[[2015-08-17]]

[[2015-08-24]]

[[2015-08-31]]

[[2015-09-08]]

[[2015-09-14]]

[[2015-09-21]]

[[2015-09-28]]

Ling Luo 2015-09-14

2015-09-15T06:20:52Z

Luoling：/* Works in last week */

== Works in last week ==
training embeddings(besides CBOW ,Skip-gram) :

Order ,Glove,NNLM,C&W,LBL

Dimensions:50

Iters:50

to find the best performance

== Works in this week ==
NLP Task:Sentence Classification bansed on CNN (2014) running on theano

Some python scripts to operate on the results and data automatically

Ling Luo 2015-09-14

2015-09-15T06:19:49Z

Luoling：以“== Works in last week == training embeddings(besides CBOW ,Skip-gram) : Order ,Glove,NNLM,C&W,LBL Dimensions:50 Iters:50 to find the best performance == Works...”为内容创建页面

== Works in last week ==
training embeddings(besides CBOW ,Skip-gram) :

Order ,Glove,NNLM,C&W,LBL
Dimensions:50
Iters:50

to find the best performance

== Works in this week ==
NLP Task:Sentence Classification bansed on CNN (2014) running on theano

Some python scripts to operate on the results and data automatically

2015-09-14

2015-09-15T05:49:50Z

Luoling：

[[Mengyuan Zhao 2015-09-14]]

[[Zhiyuan Tang 2015-09-14]]

[[Zhiyong Zhang 2015-09-14]]

[[Tianyi Luo 2015-09-14]]

[[Xuewei Zhang 2015-09-14]]

[[Askar 2015-09-14]]

[[Jun Qi 2015-09-14]]

[[Xiangyu Zeng 2015-09-14]]

[[Chao Xing 2015-09-14]]

[[Dongxu Zhang 2015-09-14]]

[[Lantian Li 2015-09-14]]

[[Rong Liu 2015-09-14]]

[[Zhihao Li 2015-09-14]]

[[Hui Tang 2015-09-14]]

[[Yang Yu 2015-09-14]]

[[Ling Luo 2015-09-14]]

Ling Luo 2015-09-07

2015-09-07T09:47:15Z

Luoling：以“ == Works in last week == sem_syn analogy task using different measure methods ner task focus on cnn == Works in this week == double-week report further op...”为内容创建页面

== Works in last week ==

sem_syn analogy task using different measure methods

ner task

focus on cnn

== Works in this week ==

double-week report

further optimization of some tasks

2015-09-08

2015-09-07T09:42:17Z

Luoling：

[[ Xiaoxi Wang 2015-09-07 ]]

[[Chao Xing 2015-09-07]]

[[Tianyi Luo 2015-09-07]]

[[Ling Luo 2015-09-07]]

Ling Luo 2015-08-31

2015-09-02T02:24:39Z

Luoling：/* Works in this week: */

== Works in the past: ==

1.''Finish training word embeddings via 5 models :''

using EnWiki dataset(953M):

CBOW,Skip-Gram

using text8 dataset(95.3M):

CBOW,Skip-Gram,C&W,GloVe,LBL and Order(count-based)

2.''Use tasks to measure quality of the word vectors with various dimensions(10~200):''

word similarity

the TOEFL set:small dataset

analogy task:9K semantic and 10.5K syntactic analogy questions

text classification:IMDB dataset——pos&neg,use unlabeled dataset to train word embeddings

sentence-level sentiment classification (based on convolutional neural networks)

part-of-speech tagging

== Works in this week: ==

semantic&syntactic analogy:
try to use different similarity calculation methods

named entity recognition

focus on cnn

Ling Luo 2015-08-31

2015-09-02T02:22:54Z

Luoling：/* Works in this week: */

== Works in the past: ==

1.''Finish training word embeddings via 5 models :''

using EnWiki dataset(953M):

CBOW,Skip-Gram

using text8 dataset(95.3M):

CBOW,Skip-Gram,C&W,GloVe,LBL and Order(count-based)

2.''Use tasks to measure quality of the word vectors with various dimensions(10~200):''

word similarity

the TOEFL set:small dataset

analogy task:9K semantic and 10.5K syntactic analogy questions

text classification:IMDB dataset——pos&neg,use unlabeled dataset to train word embeddings

sentence-level sentiment classification (based on convolutional neural networks)

part-of-speech tagging

== Works in this week: ==

word similarity:
try to use different similarity calculation methods

named entity recognition

focus on cnn

Ling Luo 2015-08-31

2015-09-02T02:22:19Z

Luoling：/* Works in the past: */

== Works in the past: ==

1.''Finish training word embeddings via 5 models :''

using EnWiki dataset(953M):

CBOW,Skip-Gram

using text8 dataset(95.3M):

CBOW,Skip-Gram,C&W,GloVe,LBL and Order(count-based)

2.''Use tasks to measure quality of the word vectors with various dimensions(10~200):''

word similarity

the TOEFL set:small dataset

analogy task:9K semantic and 10.5K syntactic analogy questions

text classification:IMDB dataset——pos&neg,use unlabeled dataset to train word embeddings

sentence-level sentiment classification (based on convolutional neural networks)

part-of-speech tagging

== Works in this week: ==

word similarity:
try to use different similarity calculation method

named entity recognition

focus on cnn

Ling Luo 2015-08-31

2015-09-02T02:21:47Z

Luoling：/* Works in this week: */

== Works in the past: ==

1.''Finish training word embeddings via 5 models :''

using EnWiki dataset(953M):

CBOW,Skip-Gram

using text8 dataset(95.3M):

CBOW,Skip-Gram,C&W,GloVe,LBL and Order(count-based)

2.''Use tasks to measure quality of the word vectors with various dimensions(10~200):''

word similarity(ws)

the TOEFL set:small dataset

analogy task:9K semantic and 10.5K syntactic analogy questions

text classification:IMDB dataset——pos&neg,use unlabeled dataset to train word embeddings

sentence-level sentiment classification (based on convolutional neural networks)

part-of-speech tagging

== Works in this week: ==

word similarity:
try to use different similarity calculation method

named entity recognition

focus on cnn

Ling Luo 2015-08-31

2015-09-02T02:19:30Z

Luoling：/* Works in the past: */

== Works in the past: ==

1.''Finish training word embeddings via 5 models :''

using EnWiki dataset(953M):

CBOW,Skip-Gram

using text8 dataset(95.3M):

CBOW,Skip-Gram,C&W,GloVe,LBL and Order(count-based)

2.''Use tasks to measure quality of the word vectors with various dimensions(10~200):''

word similarity(ws)

the TOEFL set:small dataset

analogy task:9K semantic and 10.5K syntactic analogy questions

text classification:IMDB dataset——pos&neg,use unlabeled dataset to train word embeddings

sentence-level sentiment classification (based on convolutional neural networks)

part-of-speech tagging

== Works in this week: ==

word similarity(ws):
try to use different similarity calculation method

named entity recognition(ner)

focus on cnn

Ling Luo 2015-08-31

2015-09-02T02:19:05Z

Luoling：/* Works in this week: */

== Works in the past: ==

1.''Finish training word embeddings via 5 models :''
using EnWiki dataset(953M):
CBOW,Skip-Gram
using text8 dataset(95.3M):
CBOW,Skip-Gram,C&W,GloVe,LBL and Order(count-based)

2.''Use tasks to measure quality of the word vectors with various dimensions(10~200):''
word similarity(ws)
the TOEFL set:small dataset
analogy task:9K semantic and 10.5K syntactic analogy questions
text classification:IMDB dataset——pos&neg,use unlabeled dataset to train word embeddings
sentence-level sentiment classification (based on convolutional neural networks)
part-of-speech tagging

== Works in this week: ==

word similarity(ws):
try to use different similarity calculation method

named entity recognition(ner)

focus on cnn

Ling Luo 2015-08-31

2015-09-02T02:18:25Z

Luoling：以“ == Works in the past: == 1.''Finish training word embeddings via 5 models :'' using EnWiki dataset(953M): CBOW,Skip-Gram using text8 dataset(95.3M): CBOW,Skip-Gra...”为内容创建页面

== Works in the past: ==

1.''Finish training word embeddings via 5 models :''
using EnWiki dataset(953M):
CBOW,Skip-Gram
using text8 dataset(95.3M):
CBOW,Skip-Gram,C&W,GloVe,LBL and Order(count-based)

2.''Use tasks to measure quality of the word vectors with various dimensions(10~200):''
word similarity(ws)
the TOEFL set:small dataset
analogy task:9K semantic and 10.5K syntactic analogy questions
text classification:IMDB dataset——pos&neg,use unlabeled dataset to train word embeddings
sentence-level sentiment classification (based on convolutional neural networks)
part-of-speech tagging

== Works in this week: ==

word similarity(ws):try to use different similarity calculation method
named entity recognition(ner)
focus on cnn

2015-08-31

2015-09-02T02:04:35Z

Luoling：

[[Jun Qi 2015-08-31]]

[[Mengyuan Zhao 2015-08-31]]

[[Tianyi Luo 2015-08-31]]

[[Ke Ning 2015-08-31]]

[[Chao Xing 2015-08-31]]

[[Haichao Yu 2015-08-31]]

[[Xuewei Zhang 2015-08-31]]

[[Rong Liu 2015-08-31]]

[[Hui Tang 2015-08-31]]

[[Yang Yu 2015-08-31]]

[[Lantian Li 2015-08-31]]

[[Zhiyuan Tang 2015-08-31]]

[[Zhiyong Zhang 2015-08-31]]

[[Dongxu Zhang 2015-08-31]]

[[Xiaoxi Wang 2015-08-31]]

[[Chaoyuan Zuo 2015-08-31]]

[[Ling Luo 2015-08-31]]

讨论:2015-08-17

2015-08-19T04:53:41Z

Luoling：清空页面

讨论:2015-08-17

2015-08-19T04:52:12Z

Luoling：Luo Ling 2015-08-17

Works in This week:

1.Finish training word embeddings via 5 models :
using EnWiki dataset(953M):
CBOW,Skip-Gram(SG)
using text8 dataset(95.3M):
CBOW,Skip-Gram(SG),C&W,GloVe,LBL and Order(count-based)

2.Use tasks to measure quality of the word vectors with various dimensions:
word similarity(ws)
the TOEFL set
analogy task
text classification
named entity recognition(ner)
sentence-level sentiment classification (based on convolutional neural networks),just call it 'cnn'
part-of-speech tagging(pos)