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Categorization
Results: 966

#	Item
551	XJTU at TRECVID2008 High-Level Feature Extraction Zhe Wang, Guizhong Liu, Xueming Qian, Zhi Li, DanPing Guo, Nan Nan, Huaixia Jiang Signal Processing Multi-Disciplinary Research Center, School of Electronic and Informati Add to Reading List Source URL: www-nlpir.nist.gov Language: English - Date: 2008-12-03 08:54:12 Vision Color histogram Support vector machine Histogram AdaBoost Feature Classifier Bag of words model in computer vision Boosting methods for object categorization Statistics Computer vision Artificial intelligence
552	Incident Training Scenarios In keeping with the “Train the Trainer” approach, the purpose of this document is to provide agencies with scenarios that allow staff to practice incident categorization. The scenarios bel Add to Reading List Source URL: www.mass.gov Language: English - Date: 2014-04-11 16:07:53 Wheelchair Wheelchairs Electric vehicles Motorized wheelchair
553	Oxford-IIIT TRECVID 2010 – Notebook Paper Mayank Juneja, Siddhartha Chandra, Omkar M. Parkhi, C. V. Jawahar Center for Visual Information Technology, International Institute of Information Technology, Gachibowli, Hyder Add to Reading List Source URL: www-nlpir.nist.gov Language: English - Date: 2011-03-04 14:18:39 Computer vision Statistical classification Ensemble learning Support vector machine Classifier Random forest Key frame Feature Boosting methods for object categorization Machine learning Statistics Artificial intelligence
554	Journal of Machine Learning Research[removed] Published 2/08 Response to Mease and Wyner, Evidence Contrary to the Statistical View of Boosting, JMLR 9:131–156, 2008: And Yet It Overfits Add to Reading List Source URL: www.stat.berkeley.edu Language: English - Date: 2009-03-21 03:28:48 Boosting Statistical classification Classification rule Artificial neuron Boosting methods for object categorization Margin classifier Machine learning Ensemble learning AdaBoost
555	PKU@TRECVID2009: Single-Actor and Pair-Activity Event Detection in Surveillance Video Zhipeng Hu a, Guangnan Ye b, Guochen Jia a, Xibin Chen b, Qiong Hu c, Kaihua Jiang b, Yaowei Wang a, d, Lei Qing c, Yonghong Tian a, X Add to Reading List Source URL: www-nlpir.nist.gov Language: English - Date: 2010-04-14 09:58:22 Face recognition Pedestrian detection Optical flow Support vector machine Boosting methods for object categorization Computer vision Surveillance Face detection
556	TZI Bremen - Trecvid 2006 high level feature extraction A. Bruckmann M. Buczilowski B. Lerbs D. Gao Add to Reading List Source URL: www-nlpir.nist.gov Language: English - Date: 2006-12-07 11:18:17 Statistical classification Learning Parts of speech Support vector machine Classifier Supervised learning Boosting methods for object categorization Random subspace method Machine learning Statistics Artificial intelligence
557	TRECVID 2007 by the Brno Group High Level Feature Extraction & Shot Boundary Detection Adam Herout, Vítězslav Beran, Michal Hradiš, Igor Potúček, Pavel Zemčík, Petr Chmelař Add to Reading List Source URL: www-nlpir.nist.gov Language: English - Date: 2008-03-03 10:55:06 Learning Statistical classification Machine learning Computer vision AdaBoost Support vector machine Boosting Feature Boosting methods for object categorization Artificial intelligence Statistics Ensemble learning
558	DOC Document Add to Reading List Source URL: conf.sabanciuniv.edu Language: English - Date: 2010-03-29 04:20:12 Behavioural sciences Ingroups and outgroups In-group–out-group bias Social identity theory Minimal group paradigm Stereotype Self-categorization theory Group dynamics Group conflict Group processes Social psychology Behavior
559	POOF: Part-Based One-vs-One Features for Fine-Grained Categorization, Face Verification, and Attribute Estimation Thomas Berg Columbia University Peter N. Belhumeur Add to Reading List Source URL: thomasberg.org Language: English - Date: 2013-10-20 17:34:55 Statistical classification Computer vision Linear classifier Ensemble learning Histogram of oriented gradients Classifier Supervised learning Random forest Support vector machine Machine learning Statistics Artificial intelligence
560	Multiple Component Learning for Object Detection Piotr Doll´ ar1,2 Boris Babenko2 Serge Belongie1,2 Pietro Perona1 Zhuowen Tu3 1 Add to Reading List Source URL: authors.library.caltech.edu Language: English - Date: 2014-08-22 16:26:50 Learning Machine learning Statistical classification AdaBoost Supervised learning Boosting Classifier Support vector machine Boosting methods for object categorization Ensemble learning Statistics Artificial intelligence

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