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ICCV
2005
IEEE
15 years 8 months ago
Contour-Based Learning for Object Detection
We present a novel categorical object detection scheme that uses only local contour-based features. A two-stage, partially supervised learning architecture is proposed: a rudiment...
Jamie Shotton, Andrew Blake, Roberto Cipolla
124
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CVPR
2006
IEEE
16 years 4 months ago
Learning Semantic Patterns with Discriminant Localized Binary Projections
In this paper, we present a novel approach to learning semantic localized patterns with binary projections in a supervised manner. The pursuit of these binary projections is refor...
Shuicheng Yan, Tianqiang Yuan, Xiaoou Tang
CVPR
2005
IEEE
16 years 4 months ago
Semi-Supervised Learning Based Object Detection in Aerial Imagery
Object detection in aerial imagery has been well studied in computer vision for years. However, given the complexity of large variations of the appearance of the object and the ba...
Jian Yao, Zhongfei (Mark) Zhang
ICTAI
2008
IEEE
15 years 9 months ago
Veritas: Combining Expert Opinions without Labeled Data
We consider a variation of the problem of combining expert opinions for the situation in which there is no ground truth to use for training. Even though we don’t have labeled da...
Sharath R. Cholleti, Sally A. Goldman, Avrim Blum,...
VIP
2003
15 years 3 months ago
Using Dual Cascading Learning Frameworks for Image Indexing
To bridge the semantic gap in content-based image retrieval, detecting meaningful visual entities (e.g. faces, sky, foliage, buildings etc) in image content and classifying images...
Joo-Hwee Lim, Jesse S. Jin