Zobrazeno 1 - 10
of 4 540
pro vyhledávání: '"3D object"'
Publikováno v:
Shanghai Jiaotong Daxue xuebao, Vol 58, Iss 11, Pp 1826-1834 (2024)
To solve the problem of inadequate perception of autonomous driving in occlusion and over-the-horizon scenarios, a vehicle-road collaborative perception method based on a dual-stream feature extraction network is proposed to enhance the 3D object det
Externí odkaz:
https://doaj.org/article/ab21a9cc610441699fec16a08ddfb088
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Object detection in point clouds is essential for various applications, including autonomous navigation, household robots, and augmented/virtual reality. However, during voxelization and Bird’s Eye View transformation, local point cloud da
Externí odkaz:
https://doaj.org/article/dca67bd8dc324770b0ad2bb38d0b088f
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2024, Iss 1, Pp 1-18 (2024)
Abstract As unmanned vehicle technology advances rapidly, obstacle recognition and target detection are crucial links, which directly affect the driving safety and efficiency of unmanned vehicles. In response to the inaccurate localization of small t
Externí odkaz:
https://doaj.org/article/c6d466c1f16246049fee3911cfc2e6fc
Publikováno v:
Alexandria Engineering Journal, Vol 104, Iss , Pp 46-55 (2024)
Fueled by substantial advancements in deep learning, the domain of autonomous driving is swiftly advancing towards more robust and effective intelligent systems. One of the critical challenges in this field is achieving accurate 3D object detection,
Externí odkaz:
https://doaj.org/article/070e95decc2246819aeee0b2f75a4d6c
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 6, Pp 7681-7696 (2024)
Abstract In the wave of research on autonomous driving, 3D object detection from the Bird’s Eye View (BEV) perspective has emerged as a pivotal area of focus. The essence of this challenge is the effective fusion of camera and LiDAR data into the B
Externí odkaz:
https://doaj.org/article/e90820165ff64e448f3d1310127a12be
Autor:
Oluwajuwon A. Fawole, Danda B. Rawat
Publikováno v:
AI, Vol 5, Iss 3, Pp 1255-1285 (2024)
The development of self-driving or autonomous vehicles has led to significant advancements in 3D object detection technologies, which are critical for the safety and efficiency of autonomous driving. Despite recent advances, several challenges remain
Externí odkaz:
https://doaj.org/article/2bf317f8ff894d899c119d56d19115af
Publikováno v:
Engineering Reports, Vol 6, Iss 12, Pp n/a-n/a (2024)
Abstract Three‐dimensional object detection based on the fusion of 2D image data and 3D point clouds has become a research hotspot in the field of 3D scene understanding. However, different sensor data have discrepancies in spatial position, scale,
Externí odkaz:
https://doaj.org/article/aff37d9eab004c81b4af2dcbe52dc6bf
Publikováno v:
Graphical Models, Vol 136, Iss , Pp 101233- (2024)
Point cloud completion aims to utilize algorithms to repair missing parts in 3D data for high-quality point clouds. This technology is crucial for applications such as autonomous driving and urban planning. With deep learning’s progress, the robust
Externí odkaz:
https://doaj.org/article/c6ed1ab9ec6b4821a7a8ab7d152a96c1
Autor:
Attila Juhasz, Arpad Balogh
Publikováno v:
Geodetski Vestnik, Vol 68, Iss 02, Pp 211-222 (2024)
Remote sensing technologies and GIS have become every-day practice in military historical reconstruction. Our research employed laser scanning survey in conjunction with historical data to execute a detailed reconstruction of a common part of the Hun
Externí odkaz:
https://doaj.org/article/52ab3655e38f4ed8bd8030040d27db4b
Publikováno v:
EURASIP Journal on Image and Video Processing, Vol 2024, Iss 1, Pp 1-28 (2024)
Abstract The rapid growth on the amount of generated 3D data, particularly in the form of Light Detection And Ranging (LiDAR) point clouds (PCs), poses very significant challenges in terms of data storage, transmission, and processing. Point cloud (P
Externí odkaz:
https://doaj.org/article/e07eb65358474824b16292eb73e000bd