Latent-class hough forests for 3d object detection and pose estimation
In this paper we propose a novel framework, Latent-Class Hough Forests, for 3D object
detection and pose estimation in heavily cluttered and occluded scenes. Firstly, we adapt …
detection and pose estimation in heavily cluttered and occluded scenes. Firstly, we adapt …
Learning to classify email: a survey
XL Wang - … conference on machine learning and cybernetics, 2005 - ieeexplore.ieee.org
Email communication has become widespread, but the exponential increase in spam
(unsolicited email) and the increase in the volume of email, can make the use of email for …
(unsolicited email) and the increase in the volume of email, can make the use of email for …
[PDF][PDF] Automatic Feature Decomposition for Single View Co-training.
One of the most successful semi-supervised learning approaches is co-training for multiview
data. In co-training, one trains two classifiers, one for each view, and uses the most confident …
data. In co-training, one trains two classifiers, one for each view, and uses the most confident …
phishGILLNET—phishing detection methodology using probabilistic latent semantic analysis, AdaBoost, and co-training
V Ramanathan, H Wechsler - EURASIP Journal on Information Security, 2012 - Springer
Identity theft is one of the most profitable crimes committed by felons. In the cyber space, this
is commonly achieved using phishing. We propose here robust server side methodology to …
is commonly achieved using phishing. We propose here robust server side methodology to …
[BOOK][B] Computer Vision--ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part I
The seven-volume set comprising LNCS volumes 8689-8695 constitutes the refereed
proceedings of the 13th European Conference on Computer Vision, ECCV 2014, held in …
proceedings of the 13th European Conference on Computer Vision, ECCV 2014, held in …
An interpretable semi-supervised framework for patch-based classification of breast cancer
RE Shawi, K Kilanava, S Sakr - Scientific Reports, 2022 - nature.com
Abstract Develo** effective invasive Ductal Carcinoma (IDC) detection methods remains a
challenging problem for breast cancer diagnosis. Recently, there has been notable success …
challenging problem for breast cancer diagnosis. Recently, there has been notable success …
A robust boosting tracker with minimum error bound in a co-training framework
R Liu, J Cheng, H Lu - 2009 IEEE 12th International …, 2009 - ieeexplore.ieee.org
The varying object appearance and unlabeled data from new frames are always the
challenging problem in object tracking. Recently machine learning methods are widely …
challenging problem in object tracking. Recently machine learning methods are widely …
DCPE co-training for classification
Co-training is a well-known semi-supervised learning technique that applies two basic
learners to train the data source, which uses the most confident unlabeled data to augment …
learners to train the data source, which uses the most confident unlabeled data to augment …
A study on evolution of email spam over fifteen years
Email spam is a persistent problem, especially today, with the increasing dedication and
sophistication of spammers. Even popular social media sites such as Facebook, Twitter, and …
sophistication of spammers. Even popular social media sites such as Facebook, Twitter, and …
Diverse reduct subspaces based co-training for partially labeled data
Rough set theory is an effective supervised learning model for labeled data. However, it is
often the case that practical problems involve both labeled and unlabeled data, which is …
often the case that practical problems involve both labeled and unlabeled data, which is …