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ICCV
2009
IEEE
1335views Computer Vision» more  ICCV 2009»
16 years 9 months ago
Top-Down Color Attention for Object Recognition
Generally the bag-of-words based image representation follows a bottom-up paradigm. The subsequent stages of the process: feature detection, feature description, vocabulary cons...
Fahad Shahbaz Khan, Joost van de Weijer, Maria Van...
PAMI
2006
196views more  PAMI 2006»
15 years 4 months ago
Three-Dimensional Model-Based Object Recognition and Segmentation in Cluttered Scenes
Viewpoint independent recognition of free-form objects and their segmentation in the presence of clutter and occlusions is a challenging task. We present a novel 3D model-based alg...
Ajmal S. Mian, Mohammed Bennamoun, Robyn A. Owens
GECCO
2007
Springer
187views Optimization» more  GECCO 2007»
15 years 10 months ago
Defining implicit objective functions for design problems
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examp...
Sean Hanna
ICPR
2006
IEEE
16 years 5 months ago
Object Localization Using Input/Output Recursive Neural Networks
Localizing objects in images is a difficult task and represents the first step to the solution of the object recognition problem. This paper presents a novel approach to the local...
Lorenzo Sarti, Marco Maggini, Monica Bianchini
ICCV
2005
IEEE
16 years 6 months ago
Combining Generative Models and Fisher Kernels for Object Recognition
Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in...
Alex Holub, Max Welling, Pietro Perona