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Predicting Mobile-Captured Document Images Sharpness ...
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由 QA Bui 著作2018被引用 6 次 — As a consequence, a suitable OCR output requires efforts to enhance the quality of the captured image. This leads to an increase of computation time and cost.
Predicting Mobile-Captured Document Images Sharpness Quality
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As a consequence, a suitable OCR output requires efforts to enhance the quality of the captured image. This leads to an increase of computation time and cost.
Predicting Mobile-Captured Document Images Sharpness Quality.
DBLP
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Bibliographic details on Predicting Mobile-Captured Document Images Sharpness Quality.
Predicting Mobile-Captured Document Images Sharpness Quality
Hal-Inria
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Hal-Inria
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Citer. Quang Anh Bui, David Molard, Salvatore Tabbone. Predicting Mobile-Captured Document Images Sharpness Quality. 2018 13th IAPR International Workshop on ...
Combining Focus Measure Operators to Predict OCR ...
ResearchGate
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We propose two contributions to improve OCR accuracy prediction for mobile-captured document images. First, we present 24 focus measures, never tested on ...
[PDF] Combining Focus Measure Operators to Predict OCR ...
Semantic Scholar
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Semantic Scholar
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This paper presents 24 focus measures, never tested on document images, which are fast to compute and require no training, and shows that a combination of ...
(PDF) SmartDoc-QA: A Dataset for Quality Assessment of ...
ResearchGate
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We present in this paper a dataset for quality assessment that contains both singly- and multiply-distorted document images.
arXiv:1906.01907v1 [cs.CV] 5 Jun 2019
arXiv
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arXiv
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由 H Li 著作2019被引用 11 次 — The proposed framework for document image quality assessment, consisting of three stages. Stage 1: text line detection, Stage 2: text line.
Document Image Quality Assessment: A Survey
ACM Digital Library
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ACM Digital Library
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由 A Alaei 著作2023被引用 7 次 — This article surveys research on Document Image Quality Assessment (DIQA). We first provide a detailed analysis of both subjective and objective DIQA methods.
Perceptual Quality Assessment of Smartphone Photography
OpenReview
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OpenReview
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由 Y Fang 著作被引用 365 次 — Specifically, we collect a series of human opinions for each image, including image quality, image attributes (brightness, colorfulness, contrast, noisiness, ...