Magnifier Network for Ceramic Z-directional Height Estimation with a Single Image
| Autor: | Yoonsoo Han, Hye Jin Kim, Suyoung Chi |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Monocular
Computer science 020206 networking & telecommunications 02 engineering and technology 010501 environmental sciences 01 natural sciences visual_art 0202 electrical engineering electronic engineering information engineering visual_art.visual_art_medium Point (geometry) Ceramic Single image Algorithm 0105 earth and related environmental sciences |
| Zdroj: | ICTC |
| DOI: | 10.1109/ictc49870.2020.9289392 |
| Popis: | Due to the AI development, productivity of manufactures has been increased. This paper introduces a method that detects three dimensional size defects in ceramic products using a monocular depth estimation method. Conventional depth estimation is weak to deal with two-sided biased data. This paper addresses a brand new magnifier network in order to magnify important parts among an input with various ranges. Deep neural networks have considered that they are weak to learn partial area. However, the proposed method overcomes this weak point by applying to a proposed magnifier method. In this paper, we present that the proposed method increases the performance in terms of qualitative and quantitative aspects. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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