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PHAM-YOLO Network-based Detection Method of Combustion Line of Cigarette Paper |
Received:December 13, 2023 |
DOI:10.11980/j.issn.0254-508X.2024.03.016 |
Key Words:cigarette paper combustion line detection YOLO parallel hybrid attention mechanism |
Fund Project:烟草行业标准项目“卷烟包灰性能测试方法”(2021B023);国家烟草专卖局重大科技项目“烟草行业质量监控大数据构建及应用研究”(110202101080(SJ-04))。 |
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Abstract:To determine the combustion line of cigarette paper, the dataset for cigarette combustion line detection was construct from common scenarios. To address the challenges of detecting complex backgrounds, multiple targets, varying scales, and shapes of combustion lines, a PHAM (parallel hybrid attention mechanism) was embedded into the YOLO v5 (you only look once, version 5) backbone network, and PHAM-YOLO was constructed for detecting multiple targets with varying scales and shapes in complex backgrounds. In addition, a spatial pyramid pooling fast (SPPF), the boundary box regression (BBR) module were introduced to improve the accuracy of combustion line positioning. The results showed that the proposed PHAM-YOLO network achieved the average precision mean (mAP), precision(P) and recall (R) of 99.0%, 99.8%, and 99.0%, respectively, where mAP was improved by 5.0% compared to the original model and higher than other types of target detection methods. |
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