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基於基礎語言圖像預訓練的即時特殊行人檢測技術與智慧交通號誌控制系統的融合...

潘建豪

基於基礎語言圖像預訓練的即時特殊行人檢測技術與智慧交通號誌控制系統的融合:優化城市路口安全性與交通流暢度的研究與應用 = = Integration of Real-Time Special Pedestrian Detection Technology based on Grounded Language-Image Pre-training with Intelligent Traffic Signal Control Systems:A Study and Application for Optimizing Urban Intersection Safety and Traffic Flow Efficiency /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	基於基礎語言圖像預訓練的即時特殊行人檢測技術與智慧交通號誌控制系統的融合:優化城市路口安全性與交通流暢度的研究與應用 =/ 潘建豪.
其他題名:	Integration of Real-Time Special Pedestrian Detection Technology based on Grounded Language-Image Pre-training with Intelligent Traffic Signal Control Systems:A Study and Application for Optimizing Urban Intersection Safety and Traffic Flow Efficiency /
其他題名:	Integration of Real-Time Special Pedestrian Detection Technology based on Grounded Language-Image Pre-training with Intelligent Traffic Signal Control Systems :
作者:	潘建豪
出版者:	雲林縣 :國立虎尾科技大學 , : 民113.07.,
面頁冊數:	[9], 55面 :圖, 表 ; : 30公分.;
附註:	指導教授: 蘇暉凱, 宋啟嘉.
標題:	大數據應用. -
電子資源:	電子資源

基於基礎語言圖像預訓練的即時特殊行人檢測技術與智慧交通號誌控制系統的融合:優化城市路口安全性與交通流暢度的研究與應用 = = Integration of Real-Time Special Pedestrian Detection Technology based on Grounded Language-Image Pre-training with Intelligent Traffic Signal Control Systems:A Study and Application for Optimizing Urban Intersection Safety and Traffic Flow Efficiency /
潘建豪

基於基礎語言圖像預訓練的即時特殊行人檢測技術與智慧交通號誌控制系統的融合:優化城市路口安全性與交通流暢度的研究與應用 =Integration of Real-Time Special Pedestrian Detection Technology based on Grounded Language-Image Pre-training with Intelligent Traffic Signal Control Systems:A Study and Application for Optimizing Urban Intersection Safety and Traffic Flow Efficiency /Integration of Real-Time Special Pedestrian Detection Technology based on Grounded Language-Image Pre-training with Intelligent Traffic Signal Control Systems :A Study and Application for Optimizing Urban Intersection Safety and Traffic Flow Efficiency.潘建豪. - 初版. - 雲林縣 :國立虎尾科技大學 ,民113.07. - [9], 55面 :圖, 表 ;30公分.

指導教授: 蘇暉凱, 宋啟嘉.

碩士論文--國立虎尾科技大學電機工程系碩士班.

含參考書目.

隨著城市交通的增長，交通事故和擁堵問題成為城市管理者亟需解決的難題。根據世界衛生組織報告，每年全球約有135萬人因交通事故喪生，其中行人，特別是輪椅使用者等行動不便的群體，佔很大比例。提升城市路口的安全性和交通流暢度至關重要。為此，本研究提出了一種基於基礎語言圖像預訓練的即時特殊行人檢測技術，並將其與智慧交通號誌控制系統融合，以優化城市路口的安全性和交通流暢度。在前端處理方面，我們使用了 YOLOv7 模型進行行人檢測，這是一種高效的實時物體檢測模型。後處理則採用了 GLIP 技術，結合自然語言處理和圖像處理的優勢，進一步提高行人檢測的精度和可靠性，特別是對輪椅使用者等特殊行人的檢測。智慧交通號誌控制系統通過檢測和分析行人數據動態調整交通信號的秒數，確保行人能夠安全通過馬路。本研究提供了一種創新的解決方案，不僅提高了城市路口的安全性和交通流暢度，還為未來智慧城市的發展提供了重要參考。隨著技術的進一步完善和推廣，這一系統有望在全球範圍內得到廣泛應用，實現更加安全、高效的城市交通管理。.

(平裝)Subjects--Topical Terms:

1451891
大數據應用.

基於基礎語言圖像預訓練的即時特殊行人檢測技術與智慧交通號誌控制系統的融合:優化城市路口安全性與交通流暢度的研究與應用 = = Integration of Real-Time Special Pedestrian Detection Technology based on Grounded Language-Image Pre-training with Intelligent Traffic Signal Control Systems:A Study and Application for Optimizing Urban Intersection Safety and Traffic Flow Efficiency /
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245 1 0 $a 基於基礎語言圖像預訓練的即時特殊行人檢測技術與智慧交通號誌控制系統的融合:優化城市路口安全性與交通流暢度的研究與應用 = $b Integration of Real-Time Special Pedestrian Detection Technology based on Grounded Language-Image Pre-training with Intelligent Traffic Signal Control Systems:A Study and Application for Optimizing Urban Intersection Safety and Traffic Flow Efficiency / $c 潘建豪.
246 1 1 $a Integration of Real-Time Special Pedestrian Detection Technology based on Grounded Language-Image Pre-training with Intelligent Traffic Signal Control Systems : $b A Study and Application for Optimizing Urban Intersection Safety and Traffic Flow Efficiency.
250 $a 初版.
260 # $a 雲林縣 : $b 國立虎尾科技大學 , $c 民113.07.
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504 $a 含參考書目.
520 3 $a 隨著城市交通的增長，交通事故和擁堵問題成為城市管理者亟需解決的難題。根據世界衛生組織報告，每年全球約有135萬人因交通事故喪生，其中行人，特別是輪椅使用者等行動不便的群體，佔很大比例。提升城市路口的安全性和交通流暢度至關重要。為此，本研究提出了一種基於基礎語言圖像預訓練的即時特殊行人檢測技術，並將其與智慧交通號誌控制系統融合，以優化城市路口的安全性和交通流暢度。在前端處理方面，我們使用了 YOLOv7 模型進行行人檢測，這是一種高效的實時物體檢測模型。後處理則採用了 GLIP 技術，結合自然語言處理和圖像處理的優勢，進一步提高行人檢測的精度和可靠性，特別是對輪椅使用者等特殊行人的檢測。智慧交通號誌控制系統通過檢測和分析行人數據動態調整交通信號的秒數，確保行人能夠安全通過馬路。本研究提供了一種創新的解決方案，不僅提高了城市路口的安全性和交通流暢度，還為未來智慧城市的發展提供了重要參考。隨著技術的進一步完善和推廣，這一系統有望在全球範圍內得到廣泛應用，實現更加安全、高效的城市交通管理。.
520 3 $a With the growth of urban traffic, traffic accidents and congestion have become pressing issues for city administrators. According to the World Health Organization, approximately 1.35 million people worldwide die in traffic accidents each year, with a significant proportion involving pedestrians, especially those with mobility impairments such as wheelchair users. Enhancing the safety and efficiency of urban intersections is crucial. To address this challenge, this study proposes a real-time special pedestrian detection technology based on grounded language-image pre-training, integrated with intelligent traffic signal control systems to optimize urban intersection safety and traffic flow. In terms of frontend processing, we employ the YOLOv7 model for pedestrian detection, a highly efficient real-time object detection model. For post-processing, the GLIP (Grounded Language-Image Pre-training) technique is utilized, leveraging the advantages of natural language processing and image processing to further improve the accuracy and reliability of pedestrian detection, particularly for special pedestrians like wheelchair users. The intelligent traffic signal control system dynamically adjusts signal timings based on pedestrian data analysis to ensure safe pedestrian passage. This study provides an innovative solution that not only enhances urban intersection safety and traffic flow but also serves as an important reference for the future development of smart cities. With further refinement and promotion of the technology, this system is poised to be widely adopted globally, leading to safer and more efficient urban traffic management..
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856 7 # $u https://handle.ncl.edu.tw/11296/2k6s82 $z 電子資源 $2 http