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» Learning in Computer Vision: Some Thoughts
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DAGM
2011
Springer
12 years 7 months ago
Agnostic Domain Adaptation
The supervised learning paradigm assumes in general that both training and test data are sampled from the same distribution. When this assumption is violated, we are in the setting...
Alexander Vezhnevets, Joachim M. Buhmann
CVPR
2007
IEEE
14 years 9 months ago
Kernel Sharing With Joint Boosting For Multi-Class Concept Detection
Object/scene detection by discriminative kernel-based classification has gained great interest due to its promising performance and flexibility. In this paper, unlike traditional ...
Wei Jiang, Shih-Fu Chang, Alexander C. Loui
ACCV
2007
Springer
13 years 9 months ago
A Convex Programming Approach to the Trace Quotient Problem
Abstract. The trace quotient problem arises in many applications in pattern classification and computer vision, e.g., manifold learning, low-dimension embedding, etc. The task is ...
Chunhua Shen, Hongdong Li, Michael J. Brooks
CVPR
2010
IEEE
14 years 3 months ago
Naming People from Dialog: Temporal Grouping and Weak Supervision
We address the character identification problem in movies and television videos: assigning names to faces on the screen. Most prior work on person recognition in video assumes s...
Timothee Cour, Benjamin Sapp, Akash Nagle, Ben Tas...
ICCV
2009
IEEE
15 years 11 days ago
What is the Best Multi-Stage Architecture for Object Recognition?
In many recent object recognition systems, feature extraction stages are generally composed of a filter bank, a non-linear transformation, and some sort of feature pooling layer...
Kevin Jarrett, Koray Kavukcuoglu, Marc’Aurelio R...