標(biāo)題: Titlebook: Computer Vision for Driver Assistance; Simultaneous Traffic Mahdi Rezaei,Reinhard Klette Book 2017 Springer International Publishing AG 201 [打印本頁] 作者: 緩和緊張狀況 時(shí)間: 2025-3-21 18:14
書目名稱Computer Vision for Driver Assistance影響因子(影響力)
書目名稱Computer Vision for Driver Assistance影響因子(影響力)學(xué)科排名
書目名稱Computer Vision for Driver Assistance網(wǎng)絡(luò)公開度
書目名稱Computer Vision for Driver Assistance網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Computer Vision for Driver Assistance被引頻次
書目名稱Computer Vision for Driver Assistance被引頻次學(xué)科排名
書目名稱Computer Vision for Driver Assistance年度引用
書目名稱Computer Vision for Driver Assistance年度引用學(xué)科排名
書目名稱Computer Vision for Driver Assistance讀者反饋
書目名稱Computer Vision for Driver Assistance讀者反饋學(xué)科排名
作者: entail 時(shí)間: 2025-3-21 23:32 作者: cardiovascular 時(shí)間: 2025-3-22 01:35
Samuel H. Preston,Irma T. Elo,Ira Rosenwaikele at all times, but provided automated control features of the vehicle (based on input data generated by different sensors) already enhance safety and driver comfort. We especially consider automated control features possible by using camera data.作者: 減少 時(shí)間: 2025-3-22 05:07 作者: 老人病學(xué) 時(shí)間: 2025-3-22 10:05
https://doi.org/10.1007/978-90-481-8978-6ised and unsupervised learning approaches. The chapter provides technical details for each method, discussions on the strengths and weaknesses of each method, and gives examples and various applications for each method. Material is provided to support a decision for an appropriate object detection t作者: Liability 時(shí)間: 2025-3-22 15:40 作者: Liability 時(shí)間: 2025-3-22 17:56
Data Sources for Health Demography,g method and an accurate 2D-to-3D registration technique to obtain the driver’s head pose, yawing detection, and head-nodding detection. Chapter . and this chapter present the first major objective of this book’s focus on “driver behaviour” (i.e. driver drowsiness and distraction detection). The fin作者: llibretto 時(shí)間: 2025-3-22 21:46 作者: 孤僻 時(shí)間: 2025-3-23 02:05 作者: 不溶解 時(shí)間: 2025-3-23 06:29
https://doi.org/10.1007/978-3-319-50551-0advanced driver-assistance systems; autonomous vehicles; driver distraction; driver fatigue; vehicle det作者: 強(qiáng)所 時(shí)間: 2025-3-23 11:05
978-3-319-84426-8Springer International Publishing AG 2017作者: Cocker 時(shí)間: 2025-3-23 14:43
Vision-Based Driver-Assistance Systems,le at all times, but provided automated control features of the vehicle (based on input data generated by different sensors) already enhance safety and driver comfort. We especially consider automated control features possible by using camera data.作者: 一條卷發(fā) 時(shí)間: 2025-3-23 18:35 作者: linguistics 時(shí)間: 2025-3-24 00:40 作者: conquer 時(shí)間: 2025-3-24 06:18 作者: 農(nóng)學(xué) 時(shí)間: 2025-3-24 08:33
Dávid Karácsonyi,Andrew Taylor,Deanne Birdre detailed introduction, motivations, and a review of the state-of-the-art in this area of vision-based driver-assistance systems. The chapter also discusses existing challenges and outlines the structure of the book.作者: GILD 時(shí)間: 2025-3-24 13:07
Europe, the Oldest-Old Continent,In this chapter we present and discuss the basic computer vision concepts, techniques, and mathematical background that we use in this book. The chapter introduces image notations, the concept of integral images, colour space conversions, the Hough transform for line detection, camera coordinate systems, and stereo computer vision.作者: Finasteride 時(shí)間: 2025-3-24 18:37 作者: enflame 時(shí)間: 2025-3-24 22:15 作者: Longitude 時(shí)間: 2025-3-25 02:48
1381-6446 advanced concepts in an accessible way that is suitable for .This book summarises the state of the art in computer vision-based driver and road monitoring, focussing on monocular vision technology in particular, with the aim to address challenges of driver assistance and autonomous driving systems..作者: 頂點(diǎn) 時(shí)間: 2025-3-25 05:29
https://doi.org/10.1007/978-90-481-8978-6 method, and gives examples and various applications for each method. Material is provided to support a decision for an appropriate object detection technique for computer vision applications, including driver-assistance systems.作者: 條街道往前推 時(shí)間: 2025-3-25 08:51 作者: FORGO 時(shí)間: 2025-3-25 12:24
Object Detection, Classification, and Tracking, method, and gives examples and various applications for each method. Material is provided to support a decision for an appropriate object detection technique for computer vision applications, including driver-assistance systems.作者: 公理 時(shí)間: 2025-3-25 17:45 作者: 托人看管 時(shí)間: 2025-3-25 21:07
Gerda Neyer,Gunnar Andersson,Hill Kuluon and to indirectly support our eye-state monitoring system. Experimental results obtained for the MIT-CMU dataset, Yale dataset, and our recorded videos and comparisons with standard Haar-like detectors show noticeable improvements compared to previous methods.作者: angina-pectoris 時(shí)間: 2025-3-26 01:19
Driver Drowsiness Detection,on and to indirectly support our eye-state monitoring system. Experimental results obtained for the MIT-CMU dataset, Yale dataset, and our recorded videos and comparisons with standard Haar-like detectors show noticeable improvements compared to previous methods.作者: 喃喃訴苦 時(shí)間: 2025-3-26 07:11 作者: 敵手 時(shí)間: 2025-3-26 11:51 作者: CAPE 時(shí)間: 2025-3-26 15:34
The Future of Health Demography,bove information. The ultimate goal is to prevent a traffic accident by fusing all the existing “in-out” data from inside the car cockpit and outside on the road. We aim to warn the driver in case of high-risk driving conditions and to prevent an imminent crash.作者: 使出神 時(shí)間: 2025-3-26 18:28
Vehicle Detection and Distance Estimation,d information to reach a higher degree of certainty. The proposed algorithm is able to detect vehicles ahead both at day and night, and also for a wide range of distances. Experimental results under various conditions, including sunny, rainy, foggy, or snowy weather, show that the proposed algorithm作者: 有雜色 時(shí)間: 2025-3-26 22:12
Erratum to: Computer Vision for Driver Assistance: Simultaneous Traffic and Driver Monitoring,作者: Increment 時(shí)間: 2025-3-27 04:20
The Demographic Correlates of Health Status,d information to reach a higher degree of certainty. The proposed algorithm is able to detect vehicles ahead both at day and night, and also for a wide range of distances. Experimental results under various conditions, including sunny, rainy, foggy, or snowy weather, show that the proposed algorithm作者: 抗生素 時(shí)間: 2025-3-27 06:17 作者: opalescence 時(shí)間: 2025-3-27 13:26
Vision-Based Driver-Assistance Systems,le at all times, but provided automated control features of the vehicle (based on input data generated by different sensors) already enhance safety and driver comfort. We especially consider automated control features possible by using camera data.作者: 嚴(yán)厲譴責(zé) 時(shí)間: 2025-3-27 17:38 作者: 爵士樂 時(shí)間: 2025-3-27 18:40
Object Detection, Classification, and Tracking,ised and unsupervised learning approaches. The chapter provides technical details for each method, discussions on the strengths and weaknesses of each method, and gives examples and various applications for each method. Material is provided to support a decision for an appropriate object detection t作者: 教育學(xué) 時(shí)間: 2025-3-28 00:38 作者: CANON 時(shí)間: 2025-3-28 05:59 作者: 濕潤 時(shí)間: 2025-3-28 07:13 作者: FLAX 時(shí)間: 2025-3-28 12:40 作者: nonplus 時(shí)間: 2025-3-28 16:02
Automated CPE Labeling of CVE Summaries with Machine Learningrn software tend to be more dependent on open source libraries. The largest open source of vulnerabilities is the National Vulnerability Database (NVD), which supplies developers with machine-readable vulnerabilities. However, sometimes Common Vulnerabilities and Exposures (CVE) have not been labele
