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» Evaluating learning algorithms and classifiers
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88
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ICIP
2004
IEEE
16 years 2 months ago
Identification of insect damaged wheat kernels using transmittance images
We used transmittance images and different learning algorithms to classify insect damaged and un-damaged wheat kernels. Using the histogram of the pixels of the wheat images as th...
A. Enis Çetin, Tom Pearson, Zehra Cataltepe
109
Voted
ECML
2006
Springer
15 years 4 months ago
Batch Classification with Applications in Computer Aided Diagnosis
Abstract. Most classification methods assume that the samples are drawn independently and identically from an unknown data generating distribution, yet this assumption is violated ...
Volkan Vural, Glenn Fung, Balaji Krishnapuram, Jen...
95
Voted
ICONIP
2004
15 years 2 months ago
Semi-supervised Kernel-Based Fuzzy C-Means
This paper presents a semi-supervised kernel-based fuzzy c-means algorithm called S2KFCM by introducing semi-supervised learning technique and the kernel method simultaneously into...
Daoqiang Zhang, Keren Tan, Songcan Chen
105
Voted
ICML
2010
IEEE
15 years 1 months ago
Deep networks for robust visual recognition
Deep Belief Networks (DBNs) are hierarchical generative models which have been used successfully to model high dimensional visual data. However, they are not robust to common vari...
Yichuan Tang, Chris Eliasmith
149
Voted
ICMLA
2010
14 years 10 months ago
Bayesian Classification of Flight Calls with a Novel Dynamic Time Warping Kernel
Abstract--In this paper we propose a probabilistic classification algorithm with a novel Dynamic Time Warping (DTW) kernel to automatically recognize flight calls of different spec...
Theodoros Damoulas, Samuel Henry, Andrew Farnswort...