Probabilistic Latent Document Network Embedding
ناشر:
سال
: 2014شناسه الکترونیک: 10.1109/ICCE-TW.2014.6904057
کلیدواژه(گان): computational complexity,n image classification,n image sampling,n learning (artificial intelligence),n object detection,n pattern clustering,n pedestrians,n support vector machines,n HOG features,n SURF points,n SVM-classifier,n cascade-Adaboost structure,n deformable part models,n detection failure,n k-means clustering scheme,n nonrobust features,n object detection,n pedestrian detection,n shift with importance sampling technique,n time
کالکشن
:
-
آمار بازدید
Probabilistic Latent Document Network Embedding
Show full item record
contributor author | Le, Tuan M.V. | |
contributor author | Lauw, Hady W. | |
date accessioned | 2020-03-12T22:46:38Z | |
date available | 2020-03-12T22:46:38Z | |
date issued | 2014 | |
identifier other | 7023344.pdf | |
identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/1094201 | |
format | general | |
language | English | |
publisher | IEEE | |
title | Probabilistic Latent Document Network Embedding | |
type | Conference Paper | |
contenttype | Metadata Only | |
identifier padid | 8233896 | |
subject keywords | computational complexity | |
subject keywords | n image classification | |
subject keywords | n image sampling | |
subject keywords | n learning (artificial intelligence) | |
subject keywords | n object detection | |
subject keywords | n pattern clustering | |
subject keywords | n pedestrians | |
subject keywords | n support vector machines | |
subject keywords | n HOG features | |
subject keywords | n SURF points | |
subject keywords | n SVM-classifier | |
subject keywords | n cascade-Adaboost structure | |
subject keywords | n deformable part models | |
subject keywords | n detection failure | |
subject keywords | n k-means clustering scheme | |
subject keywords | n nonrobust features | |
subject keywords | n object detection | |
subject keywords | n pedestrian detection | |
subject keywords | n shift with importance sampling technique | |
subject keywords | n time | |
identifier doi | 10.1109/ICCE-TW.2014.6904057 | |
journal title | ata Mining (ICDM), 2014 IEEE International Conference on | |
filesize | 1684229 | |
citations | 0 |