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» A Training Method with Small Computation for Classification
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136
Voted
CVPR
2010
IEEE
15 years 10 months ago
Dominant Orientation Templates for Real-Time Detection of Texture-Less Objects
We present a method for real-time 3D object detection that does not require a time consuming training stage, and can handle untextured objects. At its core, is a novel tem- plat...
Stefan Hinterstoisser, Vincent Lepetit, Slobodan I...
153
Voted
IJCAI
1989
15 years 4 months ago
Noise-Tolerant Instance-Based Learning Algorithms
Several published reports show that instancebased learning algorithms yield high classification accuracies and have low storage requirements during supervised learning application...
David W. Aha, Dennis F. Kibler
157
Voted
ICCV
2007
IEEE
15 years 7 months ago
ClassMap: Efficient Multiclass Recognition via Embeddings
In many computer vision applications, such as face recognition and hand pose estimation, we need systems that can recognize a very large number of classes. Large margin classifica...
Vassilis Athitsos, Alexandra Stefan, Quan Yuan, St...
142
Voted
ICCV
2007
IEEE
16 years 5 months ago
Graph-Cut Transducers for Relevance Feedback in Content Based Image Retrieval
Closing the semantic gap in content based image retrieval (CBIR) basically requires the knowledge of the user's intention which is usually translated into a sequence of quest...
Hichem Sahbi, Jean-Yves Audibert, Renaud Keriven
MICCAI
2002
Springer
16 years 4 months ago
Recognizing Deviations from Normalcy for Brain Tumor Segmentation
A framework is proposed for the segmentation of brain tumors from MRI. Instead of training on pathology, the proposed method trains exclusively on healthy tissue. The algorithm att...
David T. Gering, W. Eric L. Grimson, Ron Kikinis