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» Boosting Technique for Combining Cellular GP Classifiers
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ECCV
2004
Springer
15 years 12 months ago
Weak Hypotheses and Boosting for Generic Object Detection and Recognition
In this paper we describe the first stage of a new learning system for object detection and recognition. For our system we propose Boosting [5] as the underlying learning technique...
Andreas Opelt, Michael Fussenegger, Axel Pinz, Pet...
TSMC
2008
198views more  TSMC 2008»
14 years 10 months ago
Representation Plurality and Fusion for 3-D Face Recognition
In this paper, we present an extensive study of 3-D face recognition algorithms and examine the benefits of various score-, rank-, and decision-level fusion rules. We investigate f...
Berk Gökberk, Helin Dutagaci, A. Ulas, Lale A...
ICONIP
2008
14 years 11 months ago
An Evaluation of Machine Learning-Based Methods for Detection of Phishing Sites
In this paper, we present the performance of machine learning-based methods for detection of phishing sites. We employ 9 machine learning techniques including AdaBoost, Bagging, S...
Daisuke Miyamoto, Hiroaki Hazeyama, Youki Kadobaya...
RAS
2010
167views more  RAS 2010»
14 years 8 months ago
Data association and occlusion handling for vision-based people tracking by mobile robots
This paper presents an approach for tracking multiple persons on a mobile robot with a combination of colour and thermal vision sensors, using several new techniques. First, an ad...
Grzegorz Cielniak, Tom Duckett, Achim J. Lilientha...
PAMI
2012
13 years 13 days ago
Trainable Convolution Filters and Their Application to Face Recognition
—In this paper, we present a novel image classification system that is built around a core of trainable filter ensembles that we call Volterra kernel classifiers. Our system trea...
Ritwik Kumar, Arunava Banerjee, Baba C. Vemuri, Ha...