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CVPR
2012
IEEE
13 years 3 days ago
Batch mode Adaptive Multiple Instance Learning for computer vision tasks
Multiple Instance Learning (MIL) has been widely exploited in many computer vision tasks, such as image retrieval, object tracking and so on. To handle ambiguity of instance label...
Wen Li, Lixin Duan, Ivor Wai-Hung Tsang, Dong Xu
GIS
2007
ACM
15 years 10 months ago
Linear feature extraction using perceptual grouping and graph-cuts
In this paper we present a novel system for the detection and extraction of road map information from high-resolution satellite imagery. Uniquely, the proposed system is an integr...
Charalambos Poullis, Suya You, Ulrich Neumann
CORR
2010
Springer
121views Education» more  CORR 2010»
14 years 4 months ago
Deep Self-Taught Learning for Handwritten Character Recognition
Recent theoretical and empirical work in statistical machine learning has demonstrated the importance of learning algorithms for deep architectures, i.e., function classes obtaine...
Frédéric Bastien, Yoshua Bengio, Arn...
69
Voted
NIPS
2000
14 years 11 months ago
Machine Learning for Video-Based Rendering
We present techniques for rendering and animation of realistic scenes by analyzing and training on short video sequences. This work extends the new paradigm for computer animation...
Arno Schödl, Irfan A. Essa
76
Voted
TIP
2008
157views more  TIP 2008»
14 years 9 months ago
Robust Face Tracking via Collaboration of Generic and Specific Models
Significant appearance changes of objects under different orientations could cause loss of tracking, "drifting." In this paper, we present a collaborative tracking framew...
Peng Wang, Qiang Ji