biometrics systems 中文意思是什麼

biometrics systems 解釋
生物測量系統
  1. What a person is ( biometrics systems using the different distinct features of the human body, i. e. a fingerprint, the iris etc. ). enforcement of the rules

    使用者所具備的獨特生理特徵（即是以人體特徵測定系統確認使用者的指紋、眼球等等）
  2. Face recognition from images is an important subject in computer vision research and has recently received a substantial amount of attention due to its potential application to biometrics identification systems

    人臉辨識是電腦視覺研究中相當重要的領域，近年來由於生物特徵識別系統的需求日殷，使得人臉辨識之研究更受重視。
  3. The automated passenger clearance and automated vehicle clearance systems aim to revolutionise the immigration clearance processes at control points by leveraging the smart identity card and biometrics verification technologies with a view to enhancing the overall passenger and vehicle throughput

    設立旅客自助出入境檢查和車輛司機自助出入境檢查這兩個系統的目的，是要充分利用智能身份證和生物特徵識別技術，改革各管制站的出入境檢查程序，以提升管制站的旅客和車輛整體處理量。
  4. The automated passenger clearance ( apc ) and automated vehicle clearance ( avc ) systems aim to revolutionise the immigration clearance processes at control points by leveraging the smart identity card and biometrics verification technologies with a view to enhancing the overall passenger and vehicle throughput. these systems support self - service immigration clearance for smart identity card holders

    設立旅客自助出入境檢查和車輛司機自助出入境檢查這兩個系統的目的，是要充分利用智能身份證和生物特徵識別技術，改革各管制站的出入境檢查程序，以提升管制站的旅客和車輛整體處理量。
  5. 7. the automated passenger clearance and automated vehicle clearance systems aim to revolutionise the immigration clearance processes at control points by leveraging the smart identity card and biometrics verification technologies with a view to enhancing the overall passenger and vehicle throughput

    7 .設立旅客自助出入境檢查和車輛司機自助出入境檢查這兩個系統的目的，是要充分利用智能身份證和生物特徵識別技術，改革各管制站的出入境檢查程序，以提升管制站的旅客和車輛整體處理量。
  6. Secondly, in the different level of pattern recognition, we realize feature - level fusion based on neural network and score - level fusion based on multi - classifier. thirdly, some opinions about application of multi - biometrics are given and corresponding prototype systems are realized

    二、依據模式識別的不同層次，分別實現了特徵層的整合和分數層的整合，特徵層整合採用了神經網路方法，分數層整合採用了多層線性分類器方法。
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