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ICML
2004
IEEE
14 years 11 months ago
Generative modeling for continuous non-linearly embedded visual inference
Many difficult visual perception problems, like 3D human motion estimation, can be formulated in terms of inference using complex generative models, defined over high-dimensional ...
Cristian Sminchisescu, Allan D. Jepson
CVPR
2010
IEEE
14 years 6 months ago
The Role of Features, Algorithms and Data in Visual Recognition
There are many computer vision algorithms developed for visual (scene and object) recognition. Some systems focus on involved learning algorithms, some leverage millions of trainin...
Devi Parikh and C. Lawrence Zitnick
ICIP
2007
IEEE
14 years 12 months ago
Extrapolating Learned Manifolds for Human Activity Recognition
The problem of human activity recognition via visual stimuli can be approached using manifold learning, since the silhouette (binary) images of a person undergoing a smooth motion...
Tat-Jun Chin, Liang Wang, Konrad Schindler, David ...
FLAIRS
2004
13 years 11 months ago
The Optimality of Naive Bayes
Naive Bayes is one of the most efficient and effective inductive learning algorithms for machine learning and data mining. Its competitive performance in classification is surpris...
Harry Zhang
JITE
2006
94views more  JITE 2006»
13 years 10 months ago
On the Design and Development of a UML-Based Visual Environment for Novice Programmers
learning abstract computer concepts. In addition, visualization helps novices construct a mental model of concepts, which is pivotal to further comprehension and understanding. Sec...
Brian D. Moor, Fadi P. Deek