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CVPR
2011
IEEE
13 years 1 months ago
Extracting and Locating Temporal Motifs in Video Scenes Using a Hierarchical Non Parametric Bayesian Model
In this paper, we present an unsupervised method for mining activities in videos. From unlabeled video sequences of a scene, our method can automatically recover what are the recu...
Ré, mi Emonet, Jagannadan Varadarajan, Jean-Marc ...
ALMOB
2008
127views more  ALMOB 2008»
13 years 5 months ago
HuMiTar: A sequence-based method for prediction of human microRNA targets
Background: MicroRNAs (miRs) are small noncoding RNAs that bind to complementary/partially complementary sites in the 3' untranslated regions of target genes to regulate prot...
Jishou Ruan, Hanzhe Chen, Lukasz A. Kurgan, Ke Che...
DEBU
2006
163views more  DEBU 2006»
13 years 5 months ago
Towards Activity Databases: Using Sensors and Statistical Models to Summarize People's Lives
Automated reasoning about human behavior is a central goal of artificial intelligence. In order to engage and intervene in a meaningful way, an intelligent system must be able to ...
Tanzeem Choudhury, Matthai Philipose, Danny Wyatt,...
AGI
2011
12 years 9 months ago
Learning Problem Solving Skills from Demonstration: An Architectural Approach
We present an architectural approach to learning problem solving skills from demonstration, using internal models to represent problem-solving operational knowledge. Internal forwa...
Haris Dindo, Antonio Chella, Giuseppe La Tona, Mon...
MIR
2006
ACM
141views Multimedia» more  MIR 2006»
13 years 11 months ago
Mining temporal patterns of movement for video content classification
Scalable approaches to video content classification are limited by an inability to automatically generate representations of events ode abstract temporal structure. This paper pre...
Michael Fleischman, Philip DeCamp, Deb Roy