"Semin\u00E1o o oe1en\u00ED projektu GA ER 102/03/H109 v roce 2005" . "A Novel Method for Objective Image Quality Assessment using Artificial Neural Network" . "3"^^ . "1"^^ . "[11294162C38F]" . "Nov\u00E1 metoda pro objektivn\u00ED hodnocen\u00ED kvality obrazu pou3\u00EDvaj\u00EDc\u00ED umilou neuronovou s\u00ED\u0165"@cs . "A Novel Method for Objective Image Quality Assessment using Artificial Neural Network"@en . . "RIV/68407700:21230/05:03111360" . "A Novel Method for Objective Image Quality Assessment using Artificial Neural Network"@en . "P(GA102/05/2054), P(GD102/03/H109)" . "2005-10-07+02:00"^^ . . . "511014" . . "A Novel Method for Objective Image Quality Assessment using Artificial Neural Network" . "Byla vyvinuta a do modelu implementov\u00E1na nov\u00E1 metoda pro hodnocen\u00ED kvality obrazu. Model sest\u00E1v\u00E1 ze dvou hlavn\u00EDch e\u00E1st\u00ED, z bloku extrakce zkresluj\u00EDc\u00EDch parametru a z umil\u00E9 neuronov\u00E9 s\u00EDti pro vyhodnocen\u00ED tichto parametru. Bylo uk\u00E1z\u00E1no, 3e poedlo3en\u00FD model pro hodnocen\u00ED kvality obrazu mu3e dosahovat vysok\u00E9 korelace s v\u00FDsledky subjektivn\u00EDch testu."@cs . . "RIV/68407700:21230/05:03111360!RIV07-GA0-21230___" . . "Fliegel, Karel" . . "40 ; 42" . "21230" . "artificial neural networks; image compression; image quality"@en . . . "Nov\u00E1 metoda pro objektivn\u00ED hodnocen\u00ED kvality obrazu pou3\u00EDvaj\u00EDc\u00ED umilou neuronovou s\u00ED\u0165"@cs . "A novel method for image quality assessment was developed, implemented into a model and its performance was evaluated. The model consists of the two main parts: the impairment feature extraction block and ANN as a combiner. It was shown that the proposed image quality assessment model can achieve high correlation with the subjective ratings MOS."@en . "Vr1ov" . "Vysok\u00E9 u\u010Den\u00ED technick\u00E9 v Brn\u011B. Fakulta elektrotechniky a komunika\u010Dn\u00EDch technologi\u00ED" . . . . "A novel method for image quality assessment was developed, implemented into a model and its performance was evaluated. The model consists of the two main parts: the impairment feature extraction block and ANN as a combiner. It was shown that the proposed image quality assessment model can achieve high correlation with the subjective ratings MOS." . . . . . "1"^^ . . "80-214-3013-3" . "Brno" .