Zobrazeno 1 - 10
of 7 735
pro vyhledávání: '"pedestrian detection"'
Publikováno v:
Geo-spatial Information Science, Vol 27, Iss 5, Pp 1391-1404 (2024)
The increasing availability of ubiquitous sensor data on the built environment holds great potential for a new generation of travel and mobility research. Bluetooth technology, for example, is already vastly used in vehicular transportation managemen
Externí odkaz:
https://doaj.org/article/75c0d60184c64e67a8a26befa321617f
Autor:
YU Fan, ZHANG Jing
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 5, Pp 1286-1300 (2024)
Due to the large differences in the shape and scale of pedestrian targets in real-world scenarios, compared with traditional methods, which often have lower average accuracy in pedestrian detection, transformer-based networks with attention mechanism
Externí odkaz:
https://doaj.org/article/4ed3cdd1221b4752aa3719f53f159486
Publikováno v:
Systems Science & Control Engineering, Vol 12, Iss 1 (2024)
With the development of autonomous vehicles and intelligent transportation, more accurate detection of pedestrians. However, pedestrian detection suffers from occlusion and small target. First, the HorNet to improve the higher-order spatial interacti
Externí odkaz:
https://doaj.org/article/bc015e3883884553b6f30e9be247c721
Publikováno v:
IEEE Access, Vol 12, Pp 144337-144349 (2024)
Automatic driving technology has high accuracy and real-time requirements for pedestrian identification and localization. Pedestrian detection is a basic and necessary function in vision-based pedestrian detection systems and collision warning, which
Externí odkaz:
https://doaj.org/article/c9dd01e782bb4c0196867bdc106a5c96
Single-Frame Difference-Based Image Fusion Glare-Resistant Detection System in Green Energy Vehicles
Publikováno v:
IEEE Access, Vol 12, Pp 110977-110991 (2024)
Green energy vehicles often use technologies that reduce lower inherent noise. However, adverse weather condition and low visibility at night can cause a glare effect from the headlights of oncoming cars. This poses a major threat to traffic safety.
Externí odkaz:
https://doaj.org/article/59f842d7f3974563b696fb227b9ba8b9
Publikováno v:
IEEE Access, Vol 12, Pp 76392-76403 (2024)
In pedestrian detection, small-scale pedestrians often face challenges such as limited pixel values and insufficient features, often leading to wrong or missed detection. Therefore, this paper proposed a multi-scale structure perception and global co
Externí odkaz:
https://doaj.org/article/b006313ea342412f89ea9b189d5639fe
Publikováno v:
IEEE Access, Vol 12, Pp 42509-42520 (2024)
Small-scale pedestrian detection is a challenge. The main issues are as follows: 1) Troubled by their small scale, it is difficult to extract features effectively; 2) During the detection process, it is easily disturbed by background noise such as in
Externí odkaz:
https://doaj.org/article/bb95d4c82894437093da3bdaeee37f94
Publikováno v:
IEEE Access, Vol 12, Pp 9162-9176 (2024)
Accurate and robust pedestrian detection is fundamental for indoor robotic systems to navigate safely and seamlessly alongside humans in spatially constrained, unpredictable indoor environments. This paper presents a novel method, IRBGHR-PIXOR, a det
Externí odkaz:
https://doaj.org/article/4ac6c870baa54d42936c26edd278112a
Autor:
Soo-Yong Park, Seok-Cheol Kee
Publikováno v:
World Electric Vehicle Journal, Vol 15, Iss 10, p 452 (2024)
The incidence of right-turning pedestrian accidents is increasing in South Korea. Most of the accidents occur when a large vehicle is turning right, and the main cause of the accidents was found to be the driver’s limited field of vision. After the
Externí odkaz:
https://doaj.org/article/c44510fcfa094533977b7054edaa6f36
Publikováno v:
Applied Sciences, Vol 14, Iss 20, p 9588 (2024)
Pedestrian detection is a critical task in computer vision; however, mainstream algorithms often struggle to achieve high detection accuracy in complex scenarios, particularly due to target occlusion and the presence of small objects. This paper intr
Externí odkaz:
https://doaj.org/article/80500afa481f4ee89f8fac92bc1580c2