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人工智慧應用於鋪面辨識演算法訓練數據量之比較-以YOLO演算法為例 = ...

CHO, CHANG-HENG

人工智慧應用於鋪面辨識演算法訓練數據量之比較-以YOLO演算法為例 = Comparison of AI-based training data amounts for Pavement Detection - A case study on YOLO algorithm

[NT 42944] Record Type:	[NT 1579] Language materials, printed : [NT 40817] monographic
[NT 47350] Paralel Title:	Comparison of AI-based training data amounts for Pavement Detection - A case study on YOLO algorithm
[NT 47261] Author:	卓長衡,
[NT 47351] Place of Publication:	新北市
[NT 47263] Published:	撰者;
[NT 47352] Year of Publication:	2023[民112]
[NT 47264] Description:	vi,45圖表 : 30公分;
[NT 47266] Subject:	人工智慧
[NT 47266] Subject:	YOLO演算法
[NT 47266] Subject:	鋪面辨識
[NT 47266] Subject:	訓練數據量
[NT 47266] Subject:	準確率
[NT 47266] Subject:	效率
[NT 47266] Subject:	數據增強
[NT 47266] Subject:	魯棒性
[NT 47266] Subject:	路面維護
[NT 47266] Subject:	安全監控
[NT 47266] Subject:	Artificial Intelligence
[NT 47266] Subject:	Pavement Detection
[NT 47266] Subject:	YOLO Algorithm
[NT 47266] Subject:	Training Data Volume
[NT 47266] Subject:	Accuracy
[NT 47266] Subject:	Efficiency
[NT 47266] Subject:	Data Augmentation
[NT 47266] Subject:	Robustness
[NT 47266] Subject:	Road Maintenance
[NT 47266] Subject:	Safety Monitoring
[NT 51458] Online resource:	https://hdl.handle.net/11296/5cbe37
[NT 47265] Notes:	畢業學年度：111

人工智慧應用於鋪面辨識演算法訓練數據量之比較-以YOLO演算法為例 = Comparison of AI-based training data amounts for Pavement Detection - A case study on YOLO algorithm
卓, 長衡

人工智慧應用於鋪面辨識演算法訓練數據量之比較-以YOLO演算法為例 = Comparison of AI-based training data amounts for Pavement Detection - A case study on YOLO algorithm / 卓長衡撰 - 新北市 : 撰者, 2023[民112]. - vi,45 ; 圖表 ; 30公分.
畢業學年度：111.
含參考書目.
人工智慧YOLO演算法鋪面辨識訓練數據量準確率效率數據增強魯棒性路面維護安全監控Artificial IntelligencePavement DetectionYOLO AlgorithmTraining Data VolumeAccuracyEfficiencyData AugmentationRobustnessRoad MaintenanceSafety Monitoring

人工智慧應用於鋪面辨識演算法訓練數據量之比較-以YOLO演算法為例 = Comparison of AI-based training data amounts for Pavement Detection - A case study on YOLO algorithm
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328 $a 碩士論文--醒吾科技大學資訊科技應用研究所 111 $u Thesis (M.A.) -- Hsing Wu Institute of Technology, 2023
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