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PR
2007
165views more  PR 2007»
13 years 6 months ago
A trainable feature extractor for handwritten digit recognition
This article focusses on the problems of feature extraction and the recognition of handwritten digits. A trainable feature extractor based on the LeNet5 convolutional neural netwo...
Fabien Lauer, Ching Y. Suen, Gérard Bloch
PUC
2008
120views more  PUC 2008»
13 years 5 months ago
Technology scruples: why intimidation will not save the recording industry and how enchantment might
While the recording industry continues to lobby for increasingly draconian laws to protect their interests, users of digital technology continue to share files and copy protected ...
Mark Blythe, Peter C. Wright
ICCV
2011
IEEE
12 years 7 months ago
Scene Recognition and Weakly Supervised Object Localization with Deformable Part-Based Models
Weakly supervised discovery of common visual structure in highly variable, cluttered images is a key problem in recognition. We address this problem using deformable part-based mo...
Megha Pandey, Svetlana Lazebnik
CVPR
2009
IEEE
15 years 2 months ago
LidarBoost: Depth Superresolution for ToF 3D Shape Scanning
Depth maps captured with time-of-flight cameras have very low data quality: the image resolution is rather limited and the level of random noise contained in the depth maps is v...
Sebastian Schuon (Stanford University), Christian ...
CVPR
2009
IEEE
15 years 2 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...