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Deep Neural Networks for Image-Based Dietary Assessment
Published on: March 13, 2021
Product Inspection Methodology via Deep Learning: An Overview
Tae-Hyun Kim1, Hye-Rin Kim1, Yeong-Jun Cho2
1Data Science Team, Hyundai Mobis, Seoul 06141, Korea.
Abstract:
In this study, we present a framework for product quality inspection based on deep learning techniques. First, we categorize several deep learning models that can be applied to product inspection systems. In addition, we explain the steps for building a deep-learning-based inspection system in detail. Second, we address connection schemes that efficiently link deep learning models to product inspection systems. Finally, we propose an effective method that can maintain and enhance a product inspection system according to improvement goals of the existing product inspection systems. The proposed system is observed to possess good system maintenance and stability owing to the proposed methods. All the proposed methods are integrated into a unified framework and we provide detailed explanations of each proposed method. In order to verify the effectiveness of the proposed system, we compare and analyze the performance of the methods in various test scenarios. We expect that our study will provide useful guidelines to readers who desire to implement deep-learning-based systems for product inspection.

