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CVPR
2009
IEEE
15 years 3 months ago
What's It Going to Cost You?: Predicting Effort vs. Informativeness for Multi-Label Image Annotations
Active learning strategies can be useful when manual labeling effort is scarce, as they select the most informative examples to be annotated first. However, for visual category ...
Sudheendra Vijayanarasimhan (University of Texas a...
ICCV
2005
IEEE
14 years 10 months ago
An Expectation Maximization Approach to the Synergy between Image Segmentation and Object Categorization
In this work we deal with the problem of modelling and exploiting the interaction between the processes of image segmentation and object categorization. We propose a novel framewo...
Iasonas Kokkinos, Petros Maragos
ICIP
2003
IEEE
14 years 10 months ago
Road network extraction in remote sensing by a Markov object process
In this paper, we rely on the theory of marked point processes to perform an unsupervised road network extraction from optical and radar images. A road network is modeled by a Mar...
Caroline Lacoste, Xavier Descombes, Josiane Zerubi...
CVPR
2010
IEEE
14 years 5 months ago
Discriminative Clustering for Image Co-segmentation
Purely bottom-up, unsupervised segmentation of a single image into two segments remains a challenging task for computer vision. The co-segmentation problem is the process of joi...
Armand Joulin, Francis Bach, Jean Ponce
DAGM
2001
Springer
14 years 1 months ago
A New Contour-Based Approach to Object Recognition for Assembly Line Robots
A complete processing chain for visual object recognition is described in this paper. The system automatically detects individual objects on an assembly line, identifies their typ...
Markus Suing, Lothar Hermes, Joachim M. Buhmann