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李政旻
碩士論文:跨域掌紋辨識的資料擴增
碩士論文:跨域掌紋辨識的資料擴增
碩士論文:跨域掌紋辨識的資料擴增
By
李政旻
・
Taipei City, Taiwan
Connect
提出三種影像增強策略和 ResNeSt 的縮減版本來解決 cross-domain 的掌紋識別。首先我們在訓練期間使用 Optuna 框架和 TPE 採樣器對影像隨機轉換進行 hyper-parameter optimization。其次,將 ROI 影像旋轉到四個方向作為不同類別的訓練影像來 oversample 訓練資料集。這也可以用於增強我們提出的基於 test-time augmentation 的多轉換特徵比對方法。相較於以往的方法,我們可以提升22%以上的準確度,而且在三個公開的掌紋影像資料集上可以達到99.66%以上的準確度。
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李政旻
Connect
Published: Nov 29th 2022
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Tools
Python
palmprint
optuna
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