Results 21 to 30 of about 57,218 (285)
USING LEARNING VECTOR QUANTIZATION METHOD FOR AUTOMATED IDENTIFICATION OF MYCOBACTERIUM TUBERCULOSIS
Indonesian Journal of Tropical and Infectious Disease, 2015 In this paper, we are developing an automated method for the detection of tubercle bacilli in clinical specimens, principally the sputum. This investigation is the first attempt to automatically identify TB bacilli in sputum using image processing and ...
Endah Purwanti, Prihartini Widiyanti
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ADAPTIVE VECTOR QUANTIZATION FOR REINFORCEMENT LEARNING [PDF]
IFAC Proceedings Volumes, 2002 Abstract Dynamic programming methods are capable of solving reinforcement learning problems, in which an agent must improve its behavior through trial-and-error interactions with a dynamic environment. However, these computational algorithms suffer from the curse of dimensionality (Bellman, 1957) that the number of computational operations ...
Lee, SK, Mak, KL, Lau, HYK
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Nochmals zu den Wechselfällen rhodischer Politik zu Beginn des IV. Jahrhunderts v. Chr. [PDF]
, 1984 This thesis explores the possibilities of avoiding the issues generally associated with compression of noisy imagery, through the usage of vector quantization.
Funke, Peter
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ONLINE KERNEL AMGLVQ FOR ARRHYTHMIA HEARBEATS CLASSIFICATION
Jurnal Ilmiah Kursor: Menuju Solusi Teknologi Informasi, 2016 This study proposes Online Kernel Adaptive Multilayer Generalized Learning Vector Quantization (KAMGLVQ) for handling imbalanced data sets. KAMGLVQ is extended version of AMGLVQ that used kernel function to handling non-linear classification problems ...
Elly Matul Imah, R. Sulaiman
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PREDIKSI TERJANGKITNYA PENYAKIT JANTUNG DENGAN METODE LEARNING VECTOR QUANTIZATION
Media Statistika, 2010 Learning Vector Quantization (LVQ) is a method that train the competitives layer with supervised. The competitives layer will learn automatically to classify the input vector given.
Nurul Hidayati, Budi Warsito
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Analysis of Robust Soft Learning Vector Quantization and an application to Facial Expression Recognition [PDF]
, 2009 Learning Vector Quantization (LVQ) is a popular method for multiclass classification. Several variants of LVQ have been developed recently, of which Robust Soft Learning Vector Quantization (RSLVQ) is a promising one.
Biehl, Michael, de Vries, Gert-Jan
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SUBIC: A supervised, structured binary code for image search [PDF]
, 2017 For large-scale visual search, highly compressed yet meaningful representations of images are essential. Structured vector quantizers based on product quantization and its variants are usually employed to achieve such compression while minimizing the ...
Gribonval, Rémi +3 more
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Improving learning vector quantization using data reduction
IJAIN (International Journal of Advances in Intelligent Informatics), 2019 Learning Vector Quantization (LVQ) is a supervised learning algorithm commonly used for statistical classification and pattern recognition. The competitive layer in LVQ studies the input vectors and classifies them into the correct classes. The amount of
Pande Nyoman Ariyuda Semadi +1 more
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Adaptive Relevance Matrices in Learning Vector Quantization [PDF]
Neural Computation, 2009 We propose a new matrix learning scheme to extend relevance learning vector quantization (RLVQ), an efficient prototype-based classification algorithm, toward a general adaptive metric. By introducing a full matrix of relevance factors in the distance measure, correlations between different features and their importance for the classification scheme ...
Schneider, P. +2 more
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Learning from low precision samples
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2021 With advances in edge applications in industry and healthcare, machine learning models are increasingly trained on the edge. However, storage and memory infrastructure at the edge are often primitive, due to cost and real-estate constraints.
Ji In Choi +5 more
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