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» Reducing Label Complexity by Learning From Bags
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ECCV
2010
Springer
14 years 7 months ago
Supervised Label Transfer for Semantic Segmentation of Street Scenes
In this paper, we propose a robust supervised label transfer method for the semantic segmentation of street scenes. Given an input image of street scene, we first find multiple ima...
Honghui Zhang, Jianxiong Xiao, Long Quan
AAAI
2012
13 years 22 hour ago
Learning from Demonstration for Goal-Driven Autonomy
Goal-driven autonomy (GDA) is a conceptual model for creating an autonomous agent that monitors a set of expectations during plan execution, detects when discrepancies occur, buil...
Ben George Weber, Michael Mateas, Arnav Jhala
AAAI
2006
14 years 11 months ago
Automatically Labeling the Inputs and Outputs of Web Services
Information integration systems combine data from multiple heterogeneous Web services to answer complex user queries, provided a user has semantically modeled the service first. T...
Kristina Lerman, Anon Plangprasopchok, Craig A. Kn...
CICLING
2010
Springer
15 years 29 days ago
ETL Ensembles for Chunking, NER and SRL
We present a new ensemble method that uses Entropy Guided Transformation Learning (ETL) as the base learner. The proposed approach, ETL Committee, combines the main ideas of Baggin...
Cícero Nogueira dos Santos, Ruy Luiz Milidi...
FGR
2011
IEEE
288views Biometrics» more  FGR 2011»
14 years 1 months ago
Hierarchical CRF with product label spaces for parts-based models
— Non-rigid object detection is a challenging open research problem in computer vision. It is a critical part in many applications such as image search, surveillance, humancomput...
Gemma Roig, Xavier Boix Bosch, Fernando De la Torr...