Freund, Y.,
Schapire, R.E.,
A decision-theoretic generalization of on-line learning and
an application to boosting,
JCSSI(55), No. 1, 1997, pp. 119-139.
BibRef
9700
Schapire, R.E.,
Singer, Y.,
Improved boosting algorithms using confidence-rated predictions,
MachLearn(37), No. 3, December 1999, pp. 297-336.
WWW Version. Improvements where hypotheses may assign confidences to each of
their predictions.
BibRef
9912
Frossyniotis, D.,
Likas, A.C.,
Stafylopatis, A.,
A clustering method based on boosting,
PRL(25), No. 6, 19 April 2004, pp. 641-654.
WWW Version.
0405
At each boosting iteration, a new training set is created using
weighted random sampling from the original dataset. Then apply
clustering.
BibRef
Tao, Q.[Qing],
Wu, G.W.[Gao-Wei],
Wang, J.[Jue],
A generalized S-K algorithm for learning [nu]-SVM classifiers,
PRL(25), No. 10, 16 July 2004, pp. 1165-1171.
WWW Version.
0407
BibRef
Tao, Q.[Qing],
Wu, G.W.[Gao-Wei],
Wang, J.[Jue],
A new maximum margin algorithm for one-class problems and its boosting
implementation,
PR(38), No. 7, July 2005, pp. 1071-1077.
WWW Version.
0505
BibRef
Tao, Q.[Qing],
Wu, G.W.[Gao-Wei],
Wang, J.[Jue],
A general soft method for learning SVM classifiers with L1-norm penalty,
PR(41), No. 3, March 2008, pp. 939-948.
WWW Version.
0711
Support vector machines; Classification; [nu]-SVMs; Nearest points;
Gilbert's algorithms; Schlesinger-Kozinec's algorithms;
Mitchell-Dem'yanov-Malozemov's algorithms; Soft convex hulls
BibRef
Chen, S.,
Wang, X.X.,
Harris, C.J.,
Experiments With Repeating Weighted Boosting Search for Optimization in
Signal Processing Applications,
SMC-B(35), No. 4, August 2005, pp. 682-693.
IEEE DOI Link
0508
BibRef
Yin, X.C.[Xu-Cheng],
Liu, C.P.[Chang-Ping],
Han, Z.[Zhi],
Feature combination using boosting,
PRL(26), No. 14, 15 October 2005, pp. 2195-2205.
WWW Version.
0510
BibRef
Nishii, R.,
Eguchi, S.,
Supervised image classification by contextual AdaBoost based on
posteriors in neighborhoods,
GeoRS(43), No. 11, November 2005, pp. 2547-2554.
IEEE DOI Link
0512
BibRef
Kawaguchi, S.,
Nishii, R.,
Hyperspectral Image Classification by Bootstrap AdaBoost With Random
Decision Stumps,
GeoRS(45), No. 11, November 2007, pp. 3845-3851.
IEEE DOI Link
0709
BibRef
Opelt, A.[Andreas],
Pinz, A.[Axel],
Fussenegger, M.[Michael],
Auer, P.[Peter],
Generic Object Recognition with Boosting,
PAMI(28), No. 3, March 2006, pp. 416-431.
IEEE DOI Link
0602
BibRef
Earlier: A1, A3, A2, A4:
Weak Hypotheses and Boosting for Generic Object Detection and
Recognition,
ECCV04(Vol II: 71-84).
WWW Version.
0405
Extract local regions, use local descriptors. Use boosting on the feature
vectors.
Use boosting to combine features. This allows for using diverse features.
Weekly supervised.
BibRef
Opelt, A.[Andreas],
Pinz, A.[Axel],
Object Localization with Boosting and Weak Supervision for Generic
Object Recognition,
SCIA05(862-871).
Springer DOI Link
0506
BibRef
Fussenegger, M.,
Opelt, A.,
Pinz, A.,
Auer, P.,
Object recognition using segmentation for feature detection,
ICPR04(III: 41-44).
IEEE DOI Link
0409
BibRef
Fussenegger, M.[Michael],
Opelt, A.[Andreas],
Pinz, A.[Axel],
Object localization/segmentation using generic shape priors,
ICPR06(IV: 41-44).
WWW Version.
0609
BibRef
Opelt, A.[Andreas],
Pinz, A.[Axel],
Zisserman, A.[Andrew],
Learning an Alphabet of Shape and Appearance for Multi-Class Object
Detection,
IJCV(80), No. 1, October 2008, pp. xx-yy.
Springer DOI Link
0809
BibRef
Earlier:
Incremental learning of object detectors using a visual shape alphabet,
CVPR06(I: 3-10).
IEEE DOI Link
0606
Award, CVPR, HM.
BibRef
And:
A Boundary-Fragment-Model for Object Detection,
ECCV06(II: 575-588).
Springer DOI Link
0608
BibRef
Wang, X.[Xiao],
Wang, H.[Han],
Classification by evolutionary ensembles,
PR(39), No. 4, April 2006, pp. 595-607.
WWW Version.
0604
Multiple classifier system; Genetic algorithms;
Evolutionary learning; Classifier combination; AdaBoost; Bagging
BibRef
McDonald, R.A.[Ross A.],
The mean subjective utility score, a novel metric for cost-sensitive
classifier evaluation,
PRL(27), No. 13, 1 October 2006, pp. 1472-1477.
WWW Version.
0606
Cost-sensitivity; Cost matrix; Utility; Decision theory; Boosting
BibRef
Sun, Y.J.[Yi-Jun],
Todorovic, S.[Sinisa],
Li, J.[Jian],
Unifying multi-class AdaBoost algorithms with binary base learners
under the margin framework,
PRL(28), No. 5, 1 April 2007, pp. 631-643.
WWW Version.
0703
AdaBoost; Margin theory; Multi-class classification problem
BibRef
Le, D.D.[Duy-Dinh],
Satoh, S.[Shin'ichi],
Ent-Boost: Boosting Using Entropy Measures for Robust Object Detection,
PRL(28), No. 9, 1 July 2007, pp. 1083-1090.
WWW Version.
0704
BibRef
Earlier:
ICPR06(II: 602-605).
WWW Version.
0609
Real AdaBoost; Information theory; Entropy;
Minimum description length principle (MDLP); Variable discretization;
Object detection
BibRef
Sun, Y.M.[Yan-Min],
Kamel, M.S.[Mohamed S.],
Wong, A.K.C.[Andrew K.C.],
Wang, Y.[Yang],
Cost-sensitive boosting for classification of imbalanced data,
PR(40), No. 12, December 2007, pp. 3358-3378.
WWW Version.
0709
Classification; Class imbalance problem; AdaBoost; Cost-sensitive learning
BibRef
Pham, T.V.[Thang V.],
Smeulders, A.W.M.[Arnold W.M.],
Quadratic boosting,
PR(41), No. 1, January 2008, pp. 331-341.
WWW Version.
0710
BibRef
Earlier:
Metric tree partitioning and Taylor approximation for fast support
vector classification,
ICPR06(IV: 132-135).
WWW Version.
0609
AdaBoost; Boosting algorithm; Coordinate descent; Generalization error;
Object detection; Quadratic boosting; Randomized relabeling; VC-dimension
BibRef
Gao, J.[Jun],
Xie, Z.[Zhao],
Wu, X.D.[Xin-Dong],
Generic object recognition with regional statistical models and layer
joint boosting,
PRL(28), No. 16, December 2007, pp. 2227-2237.
WWW Version.
0711
Generic object recognition; Regional statistical models;
Layer joint boosting; Sharing-code maps; ECOC matrix
BibRef
Verschae, R.[Rodrigo],
Ruiz-del-Solar, J.[Javier],
Correa, M.[Mauricio],
A unified learning framework for object detection and classification
using nested cascades of boosted classifiers,
MVA(19), No. 2, March 2008, pp. 85-103.
Springer DOI Link
0802
BibRef
Rodriguez, J.J.[Juan J.],
Maudes, J.[Jesus],
Boosting recombined weak classifiers,
PRL(29), No. 8, 1 June 2008, pp. 1049-1059.
WWW Version.
0804
Boosting; Classifier ensembles; Decision stumps
BibRef
Zhang, C.X.[Chun-Xia],
Zhang, J.S.[Jiang-She],
RotBoost: A technique for combining Rotation Forest and AdaBoost,
PRL(29), No. 10, 15 July 2008, pp. 1524-1536.
WWW Version.
0711
Ensemble method; Base learning algorithm; AdaBoost; Rotation Forest;
Bagging; MultiBoost
BibRef
Furst, L.[Luka],
Fidler, S.[Sanja],
Leonardis, A.[Ales],
Selecting features for object detection using an Adaboost-compatible
evaluation function,
PRL(29), No. 11, 1 August 2008, pp. 1603-1612.
WWW Version.
0804
Feature selection; AdaBoost; Object detection
BibRef
Fleuret, F.[Francois],
Multi-layer boosting for pattern recognition,
PRL(30), No. 3, 1 February 2009, pp. 237-241.
Elsevier DOI Link
WWW Version.
0804
Boosting; Multi-layer perceptron; Functional gradient descent;
Convolutional network
BibRef
Šochman, J.[Jan],
Matas, J.[Jirí],
Learning Fast Emulators of Binary Decision Processes,
IJCV(83), No. 2, June 2009, pp. xx-yy.
Springer DOI Link
0903
BibRef
Earlier:
Learning a Fast Emulator of a Binary Decision Process,
ACCV07(II: 236-245).
Springer DOI Link
0711
BibRef
Earlier:
WaldBoost: Learning for Time Constrained Sequential Detection,
CVPR05(II: 150-156).
IEEE DOI Link
0507
BibRef
Earlier:
Inter-stage feature propagation in cascade building with adaboost,
ICPR04(I: 236-239).
IEEE DOI Link
0409
BibRef
Lu, Y.J.[Yi-Juan],
Tian, Q.[Qi],
Discriminant Subspace Analysis: An Adaptive Approach for Image
Classification,
MultMed(11), No. 7, November 2009, pp. 1289-1300.
IEEE DOI Link
0911
BibRef
Lu, Y.J.[Yi-Juan],
Tian, Q.[Qi],
Huan, T.S.[Thomas S.],
Interactive Boosting for Image Classification,
MCAM07(315-324).
Springer DOI Link
0706
BibRef
Gao, C.X.[Chang-Xin],
Sang, N.[Nong],
Tang, Q.L.[Qi-Ling],
On selection and combination of weak learners in AdaBoost,
PRL(31), No. 9, 1 July 2010, pp. 991-1001.
Elsevier DOI Link
WWW Version.
1004
Adaboost algorithm; Distance related criterion; Kernel-based perceptron
BibRef
Chen, K.T.[Kuan-Ting],
Lin, K.H.[Kuan-Hung],
Kuo, Y.H.[Yin-Hsi],
Wu, Y.L.[Yi-Lun],
Hsu, W.H.[Winston H.],
Boosting image object retrieval and indexing by automatically
discovered pseudo-objects,
JVCIR(21), No. 8, November 2010, pp. 815-825.
Elsevier DOI Link
WWW Version.
1011
Image retrieval; Object retrieval; Pseudo-object; Visual word; Local
feature; Bundle feature; Indexing; Large-scale
BibRef
Lin, K.H.[Kuan-Hung],
Chen, K.T.[Kuan-Ting],
Hsu, W.H.[Winston H.],
Lee, C.J.[Chun-Jen],
Li, T.H.[Tien-Hsu],
Boosting object retrieval by estimating pseudo-objects,
ICIP09(785-788).
IEEE DOI Link
0911
BibRef
Shen, C.H.[Chun-Hua],
Li, H.[Hanxi],
On the Dual Formulation of Boosting Algorithms,
PAMI(32), No. 12, December 2010, pp. 2216-2231.
IEEE DOI Link
1011
BibRef
Earlier: A2, A1:
Boosting the Minimum Margin: LPBoost vs. AdaBoost,
DICTA08(533-539).
IEEE DOI Link
0812
BibRef
Shen, C.H.[Chun-Hua],
Wang, P.[Peng],
Li, H.[Hanxi],
LACBoost and FisherBoost: Optimally Building Cascade Classifiers,
ECCV10(II: 608-621).
Springer DOI Link
1009
BibRef
Chen, S.[Shi],
Wang, J.Q.[Jin-Qiao],
Ouyang, Y.[Yi],
Wang, B.[Bo],
Xu, C.S.[Chang-Sheng],
Lu, H.Q.[Han-Qing],
Boosting part-sense multi-feature learners toward effective object
detection,
CVIU(115), No. 3, March 2011, pp. 364-374.
Elsevier DOI Link
WWW Version.
1103
AdaBoost; Object detection; Multi-feature learners; L1-regularized
gradient boosting
BibRef
Wang, P.[Peng],
Shen, C.H.[Chun-Hua],
Barnes, N.[Nick],
Zheng, H.[Hong],
Ren, Z.[Zhang],
Asymmetric Totally-Corrective Boosting for Real-Time Object Detection,
ACCV10(I: 176-188).
Springer DOI Link
1011
BibRef
Hao, Z.H.[Zhi-Hui],
Shen, C.H.[Chun-Hua],
Barnes, N.[Nick],
Wang, B.[Bo],
Totally-Corrective Multi-class Boosting,
ACCV10(IV: 269-280).
Springer DOI Link
1011
BibRef
Shen, C.H.[Chun-Hua],
Hao, Z.H.[Zhi-Hui],
A direct formulation for totally-corrective multi-class boosting,
CVPR11(2585-2592).
IEEE DOI Link
1106
BibRef
Zhou, J.[Jun],
Fu, Z.Y.[Zhou-Yu],
Robles-Kelly, A.[Antonio],
Structured learning approach to image descriptor combination,
IET-CV(5), No. 2, 2011, pp. 134-142.
WWW Version.
1103
BibRef
Earlier:
Learning the Optimal Transformation of Salient Features for Image
Classification,
DICTA09(125-131).
IEEE DOI Link
0912
Combine descriptors.
BibRef
Fu, Z.Y.[Zhou-Yu],
Caelli, T.M.[Terry M.],
Liu, N.J.[Nian-Jun],
Robles-Kelly, A.[Antonio],
Boosted Band Ratio Feature Selection for Hyperspectral Image
Classification,
ICPR06(I: 1059-1062).
WWW Version.
0609
BibRef
Zhang, K.[Ke],
Jin, H.D.[Hui-Dong],
Fu, Z.Y.[Zhou-Yu],
Liu, N.J.[Nian-Jun],
Optimal Learning High-Order Markov Random Fields Priors of Colour Image,
ACCV07(I: 482-491).
Springer DOI Link
0711
BibRef
Landesa-Vázquez, I.[Iago],
Alba-Castro, J.L.[José Luis],
Shedding light on the asymmetric learning capability of AdaBoost,
PRL(33), No. 3, 1 February 2012, pp. 247-255.
Elsevier DOI Link
WWW Version.
1201
AdaBoost; Asymmetry; Boosting; Classification; Cost
BibRef
Bi, J.[Jinbo],
Wu, D.[Dijia],
Lu, L.[Le],
Liu, M.[Meizhu],
Tao, Y.[Yimo],
Wolf, M.[Matthias],
AdaBoost on low-rank PSD matrices for metric learning,
CVPR11(2617-2624).
IEEE DOI Link
1106
BibRef
Danielsson, O.[Oscar],
Carlsson, S.[Stefan],
Projectable classifiers for multi-view object class recognition,
3DRR11(577-584).
IEEE DOI Link
1201
BibRef
Danielsson, O.[Oscar],
Rasolzadeh, B.[Babak],
Carlsson, S.[Stefan],
Gated classifiers: Boosting under high intra-class variation,
CVPR11(2673-2680).
IEEE DOI Link
1106
BibRef
Saberian, M.J.[Mohammad J.],
Masnadi-Shirazi, H.[Hamed],
Vasconcelos, N.[Nuno],
TaylorBoost:
First and second-order boosting algorithms with explicit margin control,
CVPR11(2929-2934).
IEEE DOI Link
1106
BibRef
Moreno, P.[Plinio],
Ribeiro, P.C.[Pedro Canotilho],
Santos-Victor, J.[José],
Feature Set Search Space for FuzzyBoost Learning,
IbPRIA11(248-255).
Springer DOI Link
1106
See also Feature Selection for Tracker-Less Human Activity Recognition.
BibRef
Ehlers, A.[Arne],
Baumann, F.[Florian],
Spindler, R.[Ralf],
Glasmacher, B.[Birgit],
Rosenhahn, B.[Bodo],
PCA Enhanced Training Data for Adaboost,
CAIP11(I: 410-419).
Springer DOI Link
1109
BibRef
Baumann, F.[Florian],
Ernst, K.[Katharina],
Ehlers, A.[Arne],
Rosenhahn, B.[Bodo],
Symmetry Enhanced Adaboost,
ISVC10(I: 286-295).
Springer DOI Link
1011
BibRef
Jhuo, I.H.[I-Hong],
Lee, D.T.,
Boosted Multiple Kernel Learning for Scene Category Recognition,
ICPR10(3504-3507).
IEEE DOI Link
1008
BibRef
Jin, X.B.[Xiao-Bo],
Hou, X.W.[Xin-Wen],
Liu, C.L.[Cheng-Lin],
Multi-class AdaBoost with Hypothesis Margin,
ICPR10(65-68).
IEEE DOI Link
1008
BibRef
Zhang, Z.M.[Zi-Ming],
Warrell, J.[Jonathan],
Torr, P.H.S.[Philip H. S.],
Proposal generation for object detection using cascaded ranking SVMs,
CVPR11(1497-1504).
IEEE DOI Link
1106
BibRef
Warrell, J.[Jonathan],
Torr, P.H.S.[Philip H. S.],
Multiple-Instance Learning with Structured Bag Models,
EMMCVPR11(369-384).
Springer DOI Link
1107
BibRef
Warrell, J.[Jonathan],
Torr, P.H.S.[Philip H.S.],
Prince, S.J.D.[Simon J.D.],
Styp-boost: A Bilinear Boosting Algorithm for Learning
Style-parameterized Classifiers,
BMVC10(xx-yy).
HTML Version.
1009
BibRef
Sternig, S.[Sabine],
Godec, M.[Martin],
Roth, P.M.[Peter M.],
Bischof, H.[Horst],
TransientBoost: On-line boosting with transient data,
OLCV10(22-27).
IEEE DOI Link
1006
BibRef
Yamauchi, Y.[Yuji],
Matsushima, C.[Chika],
Yamashita, T.[Takayoshi],
Fujiyoshi, H.[Hironobu],
Relational HOG feature with wild-card for object detection,
VS11(1785-1792).
IEEE DOI Link
1201
BibRef
Yamauchi, Y.[Yuji],
Takaki, M.[Masanari],
Yamashita, T.[Takayoshi],
Fujiyoshi, H.[Hironobu],
Feature co-occurrence representation based on boosting for object
detection,
SISM10(31-38).
IEEE DOI Link
1006
BibRef
Zhang, B.[Bang],
Ye, G.[Getian],
Wang, Y.[Yang],
Xu, J.[Jie],
Herman, G.[Gunawan],
Finding shareable informative patterns and optimal coding matrix for
multiclass boosting,
ICCV09(56-63).
IEEE DOI Link
0909
BibRef
Pelossof, R.[Raphael],
Jones, M.[Michael],
Vovsha, I.[Ilia],
Rudin, C.[Cynthia],
Online coordinate boosting,
Learning09(1354-1361).
IEEE DOI Link
0910
BibRef
Babenko, B.[Boris],
Yang, M.H.[Ming-Hsuan],
Belongie, S.J.[Serge J.],
A family of online boosting algorithms,
Learning09(1346-1353).
IEEE DOI Link
0910
BibRef
Liu, X.[Xi],
Shi, Z.P.[Zhi-Ping],
Shi, Z.Z.[Zhong-Zhi],
Filter object categories using CoBoost with 1st and 2nd order features,
ICIP09(309-312).
IEEE DOI Link
0911
BibRef
Ji, Y.[Yi],
Idrissi, K.[Khalid],
Baskurt, A.[Atilla],
Object categorization using boosting within Hierarchical Bayesian model,
ICIP09(317-320).
IEEE DOI Link
0911
BibRef
Mahmood, A.[Arif],
Khan, S.[Sohaib],
Early terminating algorithms for Adaboost based detectors,
ICIP09(1209-1212).
IEEE DOI Link
0911
BibRef
Venkataraman, V.[Vijay],
Porikli, F.M.[Fatih M.],
RelCom: Relational combinatorics features for rapid object detection,
OTCBVS10(23-30).
IEEE DOI Link
1006
Simple features.
BibRef
Hussein, M.[Mohamed],
Porikli, F.M.[Fatih M.],
Davis, L.S.[Larry S.],
Object detection via boosted deformable features,
ICIP09(1445-1448).
IEEE DOI Link
0911
BibRef
Allende-Cid, H.[Héctor],
Mendoza, J.[Jorge],
Allende, H.[Héctor],
Canessa, E.[Enrique],
Semi-supervised Robust Alternating AdaBoost,
CIARP09(579-586).
Springer DOI Link
0911
BibRef
Klein, D.A.[Dominik Alexander],
Schulz, D.[Dirk],
Frintrop, S.[Simone],
Boosting with a Joint Feature Pool from Different Sensors,
CVS09(63-72).
Springer DOI Link
0910
BibRef
Merler, M.[Michele],
Yan, R.[Rong],
Smith, J.R.[John R.],
Imbalanced RankBoost for efficiently ranking large-scale image/video
collections,
CVPR09(2607-2614).
IEEE DOI Link
0906
BibRef
Zaidi, N.A.[Nayyar A.],
Suter, D.[David],
Confidence rated boosting algorithm for generic object detection,
ICPR08(1-4).
IEEE DOI Link
0812
BibRef
And:
Object Detection Using a Cascade of Classifiers,
DICTA08(600-605).
IEEE DOI Link
0812
BibRef
Jiang, Y.[Yan],
Ding, X.Q.[Xiao-Qing],
Bhattacharyya boosting,
ICPR08(1-4).
IEEE DOI Link
0812
BibRef
Seiffert, C.[Chris],
Khoshgoftaar, T.M.[Taghi M.],
Van Hulse, J.[Jason],
Napolitano, A.[Amri],
RUSBoost: Improving classification performance when training data is
skewed,
ICPR08(1-4).
IEEE DOI Link
0812
BibRef
Wang, S.J.[Shi-Jun],
Zhang, C.S.[Chang-Shui],
Collaborative learning by boosting in distributed environments,
ICPR08(1-4).
IEEE DOI Link
0812
BibRef
Wang, Z.J.[Zhan-Jun],
Fang, C.[Chi],
Ding, X.Q.[Xiao-Qing],
Asymmetric Real Adaboost,
ICPR08(1-4).
IEEE DOI Link
0812
BibRef
Chouaib, H.[Hassan],
Vincent, N.[Nicole],
Cloppet, F.[Florence],
Tabbone, S.A.[Salvatore A.],
Generic Feature Selection and Document Processing,
ICDAR09(356-360).
IEEE DOI Link
0907
BibRef
Chouaib, H.,
Terrades, O.R.[O. Ramos],
Tabbone, S.A.,
Cloppet, F.,
Vincent, N.,
Feature selection combining genetic algorithm and Adaboost classifiers,
ICPR08(1-4).
IEEE DOI Link
0812
BibRef
Jiang, Y.[Yan],
Ding, X.Q.[Xiao-Qing],
Partially Corrective AdaBoost,
SSPR08(469-478).
Springer DOI Link
0812
BibRef
Kalal, Z.[Zdenek],
Matas, J.G.[Jiri G.],
Mikolajczyk, K.[Krystian],
P-N learning:
Bootstrapping binary classifiers by structural constraints,
CVPR10(49-56).
IEEE DOI Link
1006
BibRef
Earlier:
Online learning of robust object detectors during unstable tracking,
Learning09(1417-1424).
IEEE DOI Link
0910
BibRef
Earlier:
Weighted Sampling for Large-Scale Boosting,
BMVC08(xx-yy).
PDF Version.
0809
BibRef
Pham, M.T.[Minh-Tri],
Hoang, V.D.D.[Viet-Dung D.],
Cham, T.J.[Tat-Jen],
Detection with multi-exit asymmetric boosting,
CVPR08(1-8).
IEEE DOI Link
0806
BibRef
Parag, T.[Toufiq],
Elgammal, A.M.[Ahmed M.],
Higher Order Markov Networks for Model Estimation,
ISVC11(I: 246-258).
Springer DOI Link
1109
BibRef
Parag, T.[Toufiq],
Elgammal, A.M.[Ahmed M.],
Supervised hypergraph labeling,
CVPR11(2289-2296).
IEEE DOI Link
1106
BibRef
Parag, T.[Toufiq],
Elgammal, A.M.[Ahmed M.],
A voting approach to learn affinity matrix for robust clustering,
ICIP09(2409-2412).
IEEE DOI Link
0911
BibRef
Parag, T.[Toufiq],
Porikli, F.M.[Fatih M.],
Elgammal, A.M.[Ahmed M.],
Boosting adaptive linear weak classifiers for online learning and
tracking,
CVPR08(1-8).
IEEE DOI Link
0806
BibRef
Corso, J.J.[Jason J.],
Discriminative modeling by Boosting on Multilevel Aggregates,
CVPR08(1-8).
IEEE DOI Link
0806
BibRef
Leistner, C.[Christian],
Saffari, A.[Amir],
Bischof, H.[Horst],
MIForests: Multiple-Instance Learning with Randomized Trees,
ECCV10(VI: 29-42).
Springer DOI Link
1009
BibRef
Zeisl, B.[Bernhard],
Leistner, C.[Christian],
Saffari, A.[Amir],
Bischof, H.[Horst],
On-line semi-supervised multiple-instance boosting,
CVPR10(1879-1879).
IEEE DOI Link
1006
See also Learning Features for Tracking. See also On-Line Multi-view Forests for Tracking.
BibRef
Roth, P.M.[Peter M.],
Leistner, C.[Christian],
Berger, A.[Armin],
Bischof, H.[Horst],
Multiple instance learning from multiple cameras,
WCN10(17-24).
IEEE DOI Link
1006
use the geometry (3D) from the multiple cameras starting from a small number
of positive samples.
BibRef
Leistner, C.[Christian],
Saffari, A.[Amir],
Roth, P.M.[Peter M.],
Bischof, H.[Horst],
On robustness of on-line boosting: a competitive study,
Learning09(1362-1369).
IEEE DOI Link
0910
BibRef
Saffari, A.[Amir],
Bischof, H.[Horst],
Boosting for Model-Based Data Clustering,
DAGM08(xx-yy).
Springer DOI Link
0806
BibRef
Allende-Cid, H.[Héctor],
Salas, R.[Rodrigo],
Allende, H.[Héctor],
Ñanculef, R.[Ricardo],
Robust Alternating AdaBoost,
CIARP07(427-436).
Springer DOI Link
0711
BibRef
Jin, Y.X.[Yu-Xin],
Tao, L.M.[Lin-Mi],
Xu, G.Y.[Guang-You],
Peng, Y.X.[Yu-Xin],
A Theoretical Approach to Construct Highly Discriminative Features with
Application in AdaBoost,
ACCV07(I: 748-757).
Springer DOI Link
0711
BibRef
Vella, F.[Filippo],
Lee, C.H.[Chin-Hui],
Gaglio, S.[Salvatore],
Boosting of Maximal Figure of Merit Classifiers for Automatic Image
Annotation,
ICIP07(II: 217-220).
IEEE DOI Link
0709
BibRef
Peng, S.W.[Shao-Wu],
Lin, L.[Liang],
Porway, J.[Jake],
Sang, N.[Nong],
Zhu, S.C.[Song-Chun],
Object Category Recognition Using Generative Template Boosting,
EMMCVPR07(198-212).
Springer DOI Link
0708
BibRef
Liu, W.[Wei],
Chang, S.F.[Shih-Fu],
Robust multi-class transductive learning with graphs,
CVPR09(381-388).
IEEE DOI Link
0906
BibRef
Jiang, W.[Wei],
Chang, S.F.[Shih-Fu],
Jebara, T.[Tony],
Loui, A.C.[Alexander C.],
Semantic Concept Classification by Joint Semi-supervised Learning of
Feature Subspaces and Support Vector Machines,
ECCV08(IV: 270-283).
Springer DOI Link
0810
BibRef
Jiang, W.[Wei],
Zavesky, E.[Eric],
Chang, S.F.[Shih-Fu],
Loui, A.C.[Alex C.],
Cross-domain learning methods for high-level visual concept
classification,
ICIP08(161-164).
IEEE DOI Link
0810
BibRef
Jiang, W.[Wei],
Chang, S.F.[Shih-Fu],
Loui, A.C.[Alexander C.],
Kernel Sharing With Joint Boosting For Multi-Class Concept Detection,
SLAM07(1-8).
IEEE DOI Link
0706
BibRef
Zhou, S.H.K.[Shao-Hua Kevin],
Zhou, J.H.[Jing-Hao],
Comaniciu, D.[Dorin],
A boosting regression approach to medical anatomy detection,
CVPR07(1-8).
IEEE DOI Link
0706
BibRef
Pham, M.T.[Minh-Tri],
Cham, T.J.[Tat-Jen],
Online Learning Asymmetric Boosted Classifiers for Object Detection,
CVPR07(1-8).
IEEE DOI Link
0706
BibRef
Uray, M.,
Skocaj, D.,
Roth, P.M.,
Bischof, H.,
Leonardis, A.,
Incremental LDA Learning by Combining Reconstructive and Discriminative
Approaches,
BMVC07(xx-yy).
PDF Version.
0709
See also On-line boosting-based car detection from aerial images.
BibRef
Renno, J.P.[John-Paul],
Makris, D.[Dimitrios],
Jones, G.A.[Graeme A.],
Object Classification in Visual Surveillance Using Adaboost,
VS07(1-8).
IEEE DOI Link
0706
BibRef
Kong, H.[Hui],
Teoh, E.K.[Eam Khwang],
Coupling Adaboost and Random Subspace for Diversified Fisher Linear
Discriminant,
ICARCV06(1-5).
IEEE DOI Link
0612
BibRef
Ghorayeb, H.[Hicham],
Steux, B.[Bruno],
Laurgeau, C.[Claude],
Boosted Algorithms for Visual Object Detection on Graphics Processing
Units,
ACCV06(II:254-263).
Springer DOI Link
0601
BibRef
Etyngier, P.[Patrick],
Paragios, N.[Nikos],
Keriven, R.[Renaud],
Genc, Y.[Yakup],
Audibert, J.Y.[Jean-Yves],
Radon space and Adaboost for Pose Estimation,
ICPR06(I: 421-424).
WWW Version.
0609
BibRef
Avidan, S.[Shai],
SpatialBoost: Adding Spatial Reasoning to AdaBoost,
ECCV06(IV: 386-396).
Springer DOI Link
0608
BibRef
Yuan, J.S.[Jun-Song],
Wu, Y.[Ying],
Context-aware clustering,
CVPR08(1-8).
IEEE DOI Link
0806
See also Mining Compositional Features From GPS and Visual Cues for Event Recognition in Photo Collections.
BibRef
Hao, W.[Wei],
Luo, J.B.[Jie-Bo],
Generalized Multiclass AdaBoost and Its Applications to Multimedia
Classification,
SLAM06(113).
IEEE DOI Link
0609
Extend AdaBoost from 2 classes to many.
See also Mining Compositional Features From GPS and Visual Cues for Event Recognition in Photo Collections.
BibRef
Deng, W.H.[Wei-Hong],
Hu, J.[Jiani],
Guo, J.[Jun],
Ada-Boost Algorithm, Classification, Naïve-,
ICPR06(II: 699-702).
WWW Version.
0609
Robust Fisher Linear Discriminant for dimensionality reduction
BibRef
Li, W.L.[Wei-Liang],
Gao, X.[Xiang],
Zhu, Y.[Ying],
Ramesh, V.[Visvanathan],
Boult, T.E.[Terrance E.],
On the Small Sample Performance of Boosted Classifiers,
CVPR05(II: 574-581).
IEEE DOI Link
0507
BibRef
Lyu, S.W.[Si-Wei],
Infomax Boosting,
CVPR05(I: 533-538).
IEEE DOI Link
0507
BibRef
Bar-Hillel, A.[Aharon],
Hertz, T.[Tomer],
Weinshall, D.[Daphna],
Object Class Recognition by Boosting a Part-Based Model,
CVPR05(I: 702-709).
IEEE DOI Link
0507
BibRef
Huang, X.S.[Xiang-Sheng],
Li, S.Z.[Stan Z.],
Wang, Y.S.[Yang-Sheng],
Jensen-Shannon Boosting Learning for Object Recognition,
CVPR05(II: 144-149).
IEEE DOI Link
0507
BibRef
Zhang, W.[Wei],
Yu, B.[Bing],
Zelinsky, G.J.[Gregory J.],
Samaras, D.[Dimitris],
Object Class Recognition Using Multiple Layer Boosting with
Heterogeneous Features,
CVPR05(II: 323-330).
IEEE DOI Link
0507
BibRef
Wolf, L.[Lior],
Martin, I.[Ian],
Robust Boosting for Learning from Few Examples,
CVPR05(I: 359-364).
IEEE DOI Link
0507
BibRef
Tu, Z.W.[Zhuo-Wen],
Learning Generative Models via Discriminative Approaches,
CVPR07(1-8).
IEEE DOI Link
0706
BibRef
Earlier:
Probabilistic Boosting-Tree: Learning Discriminative Models for
Classification, Recognition, and Clustering,
ICCV05(II: 1589-1596).
IEEE DOI Link
0510
BibRef
Skarbek, W.[Wladyslaw],
Kucharski, K.[Krzysztof],
Image Object Localization by AdaBoost Classifier,
ICIAR04(I: 511-518).
WWW Version.
0409
BibRef
Howe, N.R.[Nicholas R.],
Ricketson, A.[Amanda],
Improving the Boosted Correlogram,
ICIAR04(I: 803-810).
WWW Version.
0409
BibRef
He, J.R.[Jing-Rui],
Li, M.J.[Ming-Jing],
Zhang, H.J.[Hong-Jiang],
Zhang, C.S.[Chang-Shui],
W-boost and its application to web image classification,
ICPR04(I: 148-151).
IEEE DOI Link
0409
BibRef
Jiang, J.L.,
Loe, K.F.[Kia-Fock],
S-AdaBoost and Pattern Detection in Complex Environment,
CVPR03(I: 413-418).
IEEE Abstract.
0307
divide and conquer principle.
Eliminate outliers.
BibRef
Pavlovic, V.,
Model-based motion clustering using boosted mixture modeling,
CVPR04(I: 811-818).
IEEE Abstract.
0408
BibRef
Liu, C.[Ce],
Shum, H.Y.[Hueng-Yeung],
Kullback-Leibler boosting,
CVPR03(I: 587-594).
IEEE Abstract.
0307
BibRef
Pavlov, D.,
Mao, J.,
Dom, B.,
Scaling-up Support Vector Machines Using Boosting Algorithm,
ICPR00(Vol II: 219-222).
IEEE DOI Link
0009
BibRef
Eibl, G.,
Pfeiffer, K.,
How to Make AdaBoost.M1 Work for Weak Base Classifiers by
Changing Only One Line of the Code,
Conference13th European Conference on Machine Learning, 2002, pp. 72-83.
BibRef
0200
Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Syntactic Methods for Image Analysis .