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Alireza Farhangfar 的引文(13) 排序方式:
Active learning guided interactions for consistent image segmentation with reduced user interactions  
Interactive techniques leverage the expert knowledge of users to produce accurate image segmentations. However, the segmentation accuracy varies with the users. Additionally, users may require trainin......
IEEE International Symposium on Biomedical Imaging  2011
0次引用 0 0
Shell-neighbor method and its application in missing data imputation  
Data preparation is an important step in mining incomplete data. To deal with this problem, this paper introduces a new imputation approach called SN (Shell Neighbors) imputation, or simply SNI. The S......
Applied Intelligence  2011
1次引用 0 0
Anytime learning of anycost classifiers  
The classification of new cases using a predictive model incurs two types of costs—testing costs and misclassification costs. Recent research efforts have resulted in several novel algorithms that att......
Machine Learning  2011
0次引用 0 0
Improvement of Fingerprint Retrieval by a Statistical Classifier  
The topics of fingerprint classification, indexing, and retrieval have been studied extensively in the past decades. One problem faced by researchers is that in all publicly available fingerprint data......
IEEE Transactions on Information Forensics and Security  2011
3次引用 0 0
9314 POSTER The Clinical Outcome of Chinese Non-melanoma Skin Carcinoma Patients After Radiotherapy With Megavolage Electron  
Computational Statistics and Data Analysis  2011
0次引用 0 0
Predicting septic shock outcomes in a database with missing data using fuzzy modeling: Influence of pre-processing techniques on real-world data-based classification  
Real-world databases often contain missing data and existing correction algorithms deliver varying performance. Also, most modeling techniques are not suitable to deal with them automatically. In this......
IEEE International Conference on Fuzzy Systems  2011
0次引用 0 0
Learn++.MF: A random subspace approach for the missing feature problem  
We introduce Learn ++ .MF, an ensemble-of-classifiers based algorithm that employs random subspace selection to address the missing feature problem in supervised classification. Unlike most establishe......
Pattern Recognition  2010
2次引用 0 0
Impute Missing Assessments by Opinion Clustering in Multi-Criteria Group Decision Making Problems  
Abstract — Multi-criteria group decision-making and evaluation (MCGDME) method typically aggregates information in evaluation tables. For various reasons, evaluation tables (decision matrix) often inc......
European Society for Fuzzy Logic and Technology  2009
0次引用 0 0
Aprimorando Processos de Imputação Multivariada de Dados com Workflows  
Abstract� Knowledge,discovery in databases usually face the problem,of miss- ing values. Thus there are several preprocessing,mechanisms,that aim to make data imputation. However, these mechanisms nor......
Brazilian Symposium on Databases  2008
0次引用 0 0
PicShark: mitigating metadata scarcity through large-scale P2P collaboration  
With the commoditization of digital devices, personal information and media sharing is becoming a key application on the pervasive Web. In such a context, data annotation rather than data production i......
The Vldb Journal  2008
3次引用 0 0

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