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ICIAR
2004
Springer
13 years 10 months ago
Neuro-Fuzzy Method for Automated Defect Detection in Aluminium Castings
The automated flaw detection in aluminium castings consists of two steps: a) identification of potential defects using image processing techniques, and b) classification of pote...
Sergio Hernández, Doris Saez, Domingo Mery
FSS
2002
68views more  FSS 2002»
13 years 4 months ago
Unsupervised feature extraction using neuro-fuzzy approach
The present article demonstrates a way of formulating a neuro-fuzzy approach for feature extraction under unsupervised training. A fuzzy feature evaluation index for a set of feat...
Rajat K. De, Jayanta Basak, Sankar K. Pal
LREC
2010
133views Education» more  LREC 2010»
13 years 6 months ago
Improving Domain-specific Entity Recognition with Automatic Term Recognition and Feature Extraction
Domain specific entity recognition often relies on domain-specific knowledge to improve system performance. However, such knowledge often suffers from limited domain portability a...
Ziqi Zhang, José Iria, Fabio Ciravegna
ICML
2008
IEEE
14 years 5 months ago
Extracting and composing robust features with denoising autoencoders
Previous work has shown that the difficulties in learning deep generative or discriminative models can be overcome by an initial unsupervised learning step that maps inputs to use...
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pi...
CVPR
2012
IEEE
11 years 7 months ago
Unsupervised feature learning framework for no-reference image quality assessment
In this paper, we present an efficient general-purpose objective no-reference (NR) image quality assessment (IQA) framework based on unsupervised feature learning. The goal is to...
Peng Ye, Jayant Kumar, Le Kang, David S. Doermann