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학술논문

Integration of Multi-scale CAM and Attention for Weakly Supervised Defects Localization on Surface Defective Apple

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영문명
Integration of Multi-scale CAM and Attention for Weakly Supervised Defects Localization on Surface Defective Apple
발행기관
한국스마트미디어학회
저자명
Nguyen Bui Ngoc Han Ju Hwan Lee Jin Young Kim
간행물 정보
『스마트미디어저널』Vol12, No.9, 45~59쪽, 전체 15쪽
주제분류
공학 > 컴퓨터학
파일형태
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발행일자
2023.10.30
4,600

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영문 초록

Weakly supervised object localization (WSOL) is a task of localizing an object in an image using only image-level labels. Previous studies have followed the conventional class activation mapping (CAM) pipeline. However, we reveal the current CAM approach suffers from problems which cause original CAM could not capture the complete defects features. This work utilizes a convolutional neural network (CNN) pretrained on image-level labels to generate class activation maps in a multi-scale manner to highlight discriminative regions. Additionally, a vision transformer (ViT) pretrained was treated to produce multi-head attention maps as an auxiliary detector. By integrating the CNN-based CAMs and attention maps, our approach localizes defective regions without requiring bounding box or pixel-level supervision during training. We evaluate our approach on a dataset of apple images with only image-level labels of defect categories. Experiments demonstrate our proposed method aligns with several Object Detection models performance, hold a promise for improving localization.

목차

Ⅰ. 서론
Ⅰ. INTRODUCTION
Ⅱ. RELATED WORK
Ⅲ. PROPOSED METHOD
Ⅳ. EXPERIMENTS
Ⅴ. Discussion
Ⅵ. Conclusion
REFERENCES

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APA

Nguyen Bui Ngoc Han,Ju Hwan Lee,Jin Young Kim. (2023).Integration of Multi-scale CAM and Attention for Weakly Supervised Defects Localization on Surface Defective Apple. 스마트미디어저널, 12 (9), 45-59

MLA

Nguyen Bui Ngoc Han,Ju Hwan Lee,Jin Young Kim. "Integration of Multi-scale CAM and Attention for Weakly Supervised Defects Localization on Surface Defective Apple." 스마트미디어저널, 12.9(2023): 45-59

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