Image tracking for the high similarity drug tablets based on light intensity reflective energy and artificial neural network

Computational and Mathematical Methods in Medicine

Volumn 2014, Issue , 2014, Pages

  Liang, Zhongwei ^a   Zhou, Liang ^b   Liu, Xiaochu ^a   Wang, Xiaogang ^a  

^a GUANGZHOU UNIVERSITY   (China)

^b SHANGHAI LIXIN UNIVERSITY OF ACCOUNTING AND FINANCE   (China)

Author keywords

[No Author keywords available]

Indexed keywords

PATTERN RECOGNITION; TOPOGRAPHY;

DRUG PRODUCTION; EFFICIENCY AND RELIABILITY; LIGHT INTENSITY; MASS PRODUCTION; MATHEMATICAL PROPERTIES; PRODUCTION MONITORING; RANDOM DISTRIBUTION; RANDOM POSITION;

NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; CONTROLLED STUDY; DRUG MANUFACTURE; ELASTICITY; ILLUMINATION; IMAGE ANALYSIS; LIGHT INTENSITY; LIGHT INTENSITY REFLECTIVE ENERGY; MAXIMUM LIKELIHOOD METHOD; PATTERN RECOGNITION; PROBABILITY; REFERENCE VALUE; STATISTICAL ANALYSIS; SURFACE PROPERTY; TABLET; TABLET SURFACE; ALGORITHM; CALIBRATION; IMAGE PROCESSING; LIGHT; MEDICINAL CHEMISTRY; PHARMACEUTICS; PROCEDURES; REPRODUCIBILITY; STATISTICAL MODEL;

TABLET;

ALGORITHMS; CALIBRATION; CHEMISTRY, PHARMACEUTICAL; IMAGE PROCESSING, COMPUTER-ASSISTED; LIGHT; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); REPRODUCIBILITY OF RESULTS; SURFACE PROPERTIES; TABLETS; TECHNOLOGY, PHARMACEUTICAL;

EID: 84925883607     PISSN: 1748670X     EISSN: 17486718     Source Type: Journal    
DOI: 10.1155/2014/304685     Document Type: Article

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