Sciweavers

1139 search results - page 135 / 228
» Boosting strategy for classification
Sort
View
ICMCS
2010
IEEE
212views Multimedia» more  ICMCS 2010»
13 years 11 months ago
Homogeneous segmentation and classifier ensemble for audio tag annotation and retrieval
Audio tags describe different types of musical information such as genre, mood, and instrument. This paper aims to automatically annotate audio clips with tags and retrieve releva...
Hung-Yi Lo, Ju-Chiang Wang, Hsin-Min Wang
ECCV
2010
Springer
13 years 10 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
IJSI
2008
156views more  IJSI 2008»
13 years 10 months ago
Co-Training by Committee: A Generalized Framework for Semi-Supervised Learning with Committees
Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
Mohamed Farouk Abdel Hady, Friedhelm Schwenker
AI
2002
Springer
13 years 10 months ago
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Zhi-Hua Zhou, Jianxin Wu, Wei Tang
SAC
2008
ACM
13 years 9 months ago
Towards a model-driven engineering approach for developing embedded hard real-time software
Model-Driven Engineering (MDE) has been advocated as an effective way to deal with today's software complexity. MDE can be seen as an integrative approach combining existing ...
Fabiano Cruz, Raimundo S. Barreto, Lucas Cordeiro