Zobrazeno 1 - 10
of 136
pro vyhledávání: '"Xie Yiping"'
Autor:
Chen Jingwei, Ma Jukui, Gao Fangyuan, Tang Wei, Yang Dongjing, Zhang Chengling, Liang Zhao, Xie Yiping, Sun Houjun
Publikováno v:
Journal of Nematology, Vol 56, Iss 1, Pp 110-122 (2024)
Sweetpotato is an important crop whose roots are consumed by people worldwide. Meloidogyne enterolobii stands out as a highly deleterious variant among the species of root-knot nematode that causes significant damage in sweetpotato. In the present st
Externí odkaz:
https://doaj.org/article/8fdf7155e9624cbeacdaefdbea9d1f71
Autor:
Wang, Shuangyi, Lin, Haichuan, Xie, Yiping, Wang, Ziqi, Chen, Dong, Tan, Longyue, Hou, Xilong, Chen, Chen, Zhou, Xiao-Hu, Lin, Shengtao, Pan, Fei, So, Kent Chak-Yu, Hou, Zeng-Guang
Transcatheter tricuspid valve replacement (TTVR) is the latest treatment for tricuspid regurgitation and is in the early stages of clinical adoption. Intelligent robotic approaches are expected to overcome the challenges of surgical manipulation and
Externí odkaz:
http://arxiv.org/abs/2411.12478
Multibeam echo-sounder (MBES) is the de-facto sensor for bathymetry mapping. In recent years, cheaper MBES sensors and global mapping initiatives have led to exponential growth of available data. However, raw MBES data contains 1-25% of noise that re
Externí odkaz:
http://arxiv.org/abs/2409.13143
Remote Photoplethysmography (rPPG) is a non-contact method that uses facial video to predict changes in blood volume, enabling physiological metrics measurement. Traditional rPPG models often struggle with poor generalization capacity in unseen domai
Externí odkaz:
http://arxiv.org/abs/2409.12040
Facial-video based Remote photoplethysmography (rPPG) aims at measuring physiological signals and monitoring heart activity without any contact, showing significant potential in various applications. Previous deep learning based rPPG measurement are
Externí odkaz:
http://arxiv.org/abs/2409.12031
Implicit neural representations and neural rendering have gained increasing attention for bathymetry estimation from sidescan sonar (SSS). These methods incorporate multiple observations of the same place from SSS data to constrain the elevation esti
Externí odkaz:
http://arxiv.org/abs/2405.05807
Publikováno v:
IEEE ROBOTICS AND AUTOMATION LETTERS, VOL. 9, NO. 9, SEPTEMBER 2024
This research addresses the challenge of estimating bathymetry from imaging sonars where the state-of-the-art works have primarily relied on either supervised learning with ground-truth labels or surface rendering based on the Lambertian assumption.
Externí odkaz:
http://arxiv.org/abs/2404.14819
Side-scan sonar (SSS) is a lightweight acoustic sensor that is commonly deployed on autonomous underwater vehicles (AUVs) to provide high-resolution seafloor images. However, leveraging side-scan images for simultaneous localization and mapping (SLAM
Externí odkaz:
http://arxiv.org/abs/2312.13802
Acoustic sensors play an important role in autonomous underwater vehicles (AUVs). Sidescan sonar (SSS) detects a wide range and provides photo-realistic images in high resolution. However, SSS projects the 3D seafloor to 2D images, which are distorte
Externí odkaz:
http://arxiv.org/abs/2304.09243
Side-scan sonar (SSS) is a lightweight acoustic sensor that is frequently deployed on autonomous underwater vehicles (AUVs) to provide high-resolution seafloor images. However, using side-scan images to perform simultaneous localization and mapping (
Externí odkaz:
http://arxiv.org/abs/2304.01854