Three-stage deep learning system for recognizing contaminated serial numbers in hard disk drive: a comparison study with two-stage deep learning model

Chousak Chousangsuntorn; Teerawat Tongloy; Santhad Chuwongin; Siridech Boonsang

doi:10.1117/12.2631377

1 May 2022 Three-stage deep learning system for recognizing contaminated serial numbers in hard disk drive: a comparison study with two-stage deep learning model

Chousak Chousangsuntorn, Teerawat Tongloy, Santhad Chuwongin, Siridech Boonsang

Author Affiliations +

Proceedings Volume 12171, Thirteenth International Conference on Signal Processing Systems (ICSPS 2021); 1217103 (2022) https://doi.org/10.1117/12.2631377
Event: Thirteenth International Conference on Signal Processing Systems (ICSPS 2021), 2021, Shanghai, China

Abstract

The previous two-stage deep learning model for detecting and classifying misidentified serial numbers on the defect hard disk drive (HDD) slider was proposed by authors. We found that the threshold level adjusted during preprocessing process could limit the robustness of the two-stage model in large-scale manufacturing. Thus, we proposed a three-stage deep learning model comprised of 1) region of interest (ROI) detection and cropping, 2) character detection and cropping, and 3) character classification. Object detection algorithm and classification network used in this model are based on YOLO v.4 and EfficientNet-B0. The 1000 images captured by the digital camera were used for training (600 images) and validation (400 images) of the ROI detection model. The other 1000 captured images were used for testing the performance of the proposed three-stage model, then we compared them with those obtained from the previous two-stage model. The proposed three-stage model reaches F1 score = 0.997 and recovery rate up to 95.9%, while the two-stage model yields only 0.948 and 73%, respectively.

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Chousak Chousangsuntorn, Teerawat Tongloy, Santhad Chuwongin, and Siridech Boonsang "Three-stage deep learning system for recognizing contaminated serial numbers in hard disk drive: a comparison study with two-stage deep learning model", Proc. SPIE 12171, Thirteenth International Conference on Signal Processing Systems (ICSPS 2021), 1217103 (1 May 2022); https://doi.org/10.1117/12.2631377

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KEYWORDS

Performance modeling

Process modeling

Optical character recognition

Image classification

Manufacturing

Image processing

Convolutional neural networks

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