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ICPR
2006
IEEE
16 years 8 months ago
Latent Layout Analysis for Discovering Objects in Images
Latent Layout Analysis (LLA) is a novel unsupervised learning technique to discover objects in unseen images using a set of un-annotated training images. LLA defines a generative ...
David Liu, Datong Chen, Tsuhan Chen
ICPR
2006
IEEE
16 years 8 months ago
Image classification: Classifying distributions of visual features
We classify an image by generating a list of salient visual features present in the luminance channel, and matching the resulting variable-length feature list to categoryspecific ...
Prateek Sarkar
ICPR
2006
IEEE
16 years 8 months ago
A Semi-supervised SVM for Manifold Learning
Many classification tasks benefit from integrating manifold learning and semi-supervised learning. By formulating the learning task in a semi-supervised manner, we propose a novel...
Zhili Wu, Chun-hung Li, Ji Zhu, Jian Huang
ICPR
2004
IEEE
16 years 8 months ago
Relaxation Labeling Processes for Protein Secondary Structure Prediction
The prediction of protein secondary structure is a classical problem in bioinformatics, and in the past few years several machine learning techniques have been proposed to t. From...
Giacomo Colle, Marcello Pelillo
ICPR
2004
IEEE
16 years 8 months ago
Automated Visual Identification of Characters in Situation Comedies
The objectives of the work described in this paper are simply stated: given examples of a particular person and an unlabelled video, we wish to find every instance of that person ...
Andrew Zisserman, Mark Everingham