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» Selecting What Is Important: Training Visual Attention
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BVAI
2007
Springer
13 years 11 months ago
Recognition of Human Faces: From Biological to Artificial Vision
Face recognition is among the most challenging techniques for personal identity verification. Even though it is so natural for humans, there are still many hidden mechanisms which ...
Massimo Tistarelli, Linda Brodo, Andrea Lagorio, M...
ICIP
2009
IEEE
13 years 5 months ago
Selecting representative and distinctive descriptors for efficient landmark recognition
To have a robust and informative image content representation for image categorization, we often need to extract as many as possible visual features at various locations, scales a...
Sheng Gao, Joo-Hwee Lim
MM
2005
ACM
243views Multimedia» more  MM 2005»
14 years 1 months ago
Image region entropy: a measure of "visualness" of web images associated with one concept
We propose a new method to measure “visualness” of concepts, that is, what extent concepts have visual characteristics. To know which concept has visually discriminative power...
Keiji Yanai, Kobus Barnard
EUROS
2008
113views Robotics» more  EUROS 2008»
13 years 9 months ago
Measuring Motion Expressiveness in Wheeled Mobile Robots
This paper addresses the measurement of motion expressiveness in wheeled mobile robots. A neural network based supervised learning strategy is proposed as a method to fuse informat...
João Sequeira
ACCV
2010
Springer
13 years 2 months ago
Unsupervised Selective Transfer Learning for Object Recognition
Abstract. We propose a novel unsupervised transfer learning framework that utilises unlabelled auxiliary data to quantify and select the most relevant transferrable knowledge for r...
Wei-Shi Zheng, Shaogang Gong, Tao Xiang