Results 261 to 270 of about 21,772 (300)
Some of the next articles are maybe not open access.
An Analysis on Performance of Different Type Classifiers in Handling Big Data Sets
Frontiers in Artificial Intelligence and Applications, 2019Selamat Ali
exaly +2 more sources
Using Classifier diversity to handle label noise
2015 International Joint Conference on Neural Networks (IJCNN), 2015It is widely known in the machine learning community that class noise can be (and often is) detrimental to inducing a model of the data. Many current approaches use a single, often biased, measurement to determine if an instance is noisy. A biased measure may work well on certain data sets, but it can also be less effective on a broader set of data ...
Michael R. Smith 0002, Tony R. Martinez
openaire +1 more source
A Classifier Capable of Handling New Attributes
2007 IEEE Symposium on Computational Intelligence and Data Mining, 2007During knowledge acquisition, a new attribute can be added at any time. In such a case, rule generated by the training data with the former attribute set can not be used. Moreover, the rule can not be combined with the new data set with the newly added attribute(s) using the existing algorithms.
Dong-Hun Seo, Chi-Hwa Song, Won Don Lee
openaire +1 more source
Binary naive possibilistic classifiers: Handling uncertain inputs
International Journal of Intelligent Systems, 2009Summary: Possibilistic networks are graphical models particularly suitable for representing and reasoning with uncertain and incomplete information. According to the underlying interpretation of possibilistic scales, possibilistic networks are either quantitative (using product-based conditioning) or qualitative (using min-based conditioning).
Salem Benferhat, Karim Tabia
openaire +2 more sources
An Adaptive Ensemble Classifier for Handling Recurring Concepts
2019 International Multidisciplinary Information Technology and Engineering Conference (IMITEC), 2019The assumption with many learning algorithms is that the underlying distribution of the data is static. However, for many real world applications, data is streaming and collected over an extended period of time. Learning in such dynamic and nonstationary environments presents a challenge not common in static domains as the statistical properties of the
Tinofirei Museba +2 more
openaire +1 more source
Handling missing features in maximum margin Bayesian network classifiers
2012 IEEE International Workshop on Machine Learning for Signal Processing, 2012The Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) records hydroacoustic data to detect nuclear explosions1. This enables verification of the Comprehensive Nuclear-Test-Ban Treaty once it has entered into force. The detection can be considered as a classification problem discriminating noise-like, earthquake-caused and explosion-like data ...
Sebastian Tschiatschek +2 more
openaire +1 more source
A Hybrid Higher Order Neural Classifier for handling classification problems
Expert Systems with Applications, 2011In this paper, we propose a novel Hybrid Higher Order Neural Classifier (HHONC) which contains different high-order units. In contrast with conventional fully-connected higher order neural networks (HONN), our proposed method uses fewer learning parameters and allocates the best fitted model in dealing with different datasets by modifying the orders of
Mehdi Fallahnezhad +2 more
openaire +1 more source
Pedestrian Detection for Autonomous Cars: Occlusion Handling by Classifying Body Parts
2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2020In this work, we address the problem of detecting body parts of pedestrians using deep neural networks. In particular, we consider the occluded pedestrian detection problem in autonomous driving settings. While state-of-the-art deep neural models perform reasonably well for detecting full-body pedestrians, their performances are not satisfactory for ...
Muhammad Mobaidul Islam +3 more
openaire +1 more source
Improving existing cascaded face classifier by adding occlusion handling
2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication, 2012Recent face detectors used in human robot interaction are boosted cascades. These cascades can detect upright faces but are very sensible to occlusions. We propose a generic framework to handle occlusions at prediction time in a boosted cascade. The contribution is a probabilistic formulation of the cascade structure that considers the uncertainty ...
Pierre Bouges +3 more
openaire +1 more source
Monitoring and classifying evidence-based workload for profiling manual handling occupations
2011 IEEE International Conference on Industrial Engineering and Engineering Management, 2011The majority of employments with occupational musculoskeletal hazards can be classified as manual handling jobs in manufacturing and the public health sector. The purpose of this study was to monitor and classify evidence-based workload of a manual handling target group of nurses using a modified Delphi with three independent consecutive surveys.
Jan Pieter Clarys +3 more
openaire +3 more sources