A computational approach for corner and vertex detection
International Journal of Computer Vision
Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Journal of the ACM (JACM)
Prior knowledge in support vector kernels
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Statistical Image Object Recognition using Mixture Densities
Journal of Mathematical Imaging and Vision
Learning of Variability for Invariant Statistical Pattern Recognition
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Efficient Pattern Recognition Using a New Transformation Distance
Advances in Neural Information Processing Systems 5, [NIPS Conference]
Transformation Invariance in Pattern Recognition-Tangent Distance and Tangent Propagation
Neural Networks: Tricks of the Trade, this book is an outgrowth of a 1996 NIPS workshop
Local Representations and a direct Voting Scheme for Face Recognition
PRIS '01 Proceedings of the 1st International Workshop on Pattern Recognition in Information Systems: In conjunction with ICEIS 2001
Combined Classification of Handwritten Digits Using the 'Virtual Test Sample Method'
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Local versus Global Features for Content-Based Image Retrieval
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2
Deformation Models for Image Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Delay learning and polychronization for reservoir computing
Neurocomputing
Face verification competition on the XM2VTS database
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Beta mixture models and the application to image classification
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A novel robust kernel for visual learning problems
Neurocomputing
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Statistical classification using tangent vectors and classification based on local features are two successful methods for various image recognition problems. These two approaches tolerate global and local transformations of the images, respectively. Tangent vectors can be used to obtain global invariance with respect to small affine transformations and line thickness, for example. On the other hand, a classifier based on local representations admits the distortion of parts of the image. From these properties, a combination of the two approaches seems veryl ikely to improve on the results of the individual approaches. In this paper, we show the benefits of this combination byap plying it to the well known USPS handwritten digits recognition task. An error rate of 2.0% is obtained, which is the best result published so far for this dataset.