Zobrazeno 1 - 10
of 19 516
pro vyhledávání: '"Xiangming An"'
Publikováno v:
Mitochondrial DNA. Part B. Resources, Vol 7, Iss 1, Pp 188-190 (2022)
Erigeron annuus (L.) Pers. (annual, daisy or tall fleabane) is an annual herb native to North America but has been introduced and naturalized worldwide. In this study, its complete chloroplast (cp) genome was assembled from Illumina sequencing reads.
Externí odkaz:
https://doaj.org/article/30695876643743dd88a95aeaff267ff1
Autor:
Yan, Ji, Li, Jiwei, He, X. T., Wang, Lifeng, Chen, Yaohua, Wang, Feng, Han, Xiaoying, Pan, Kaiqiang, Liang, Juxi, Li, Yulong, Guan, Zanyang, Liu, Xiangming, Che, Xingsen, Chen, Zhongjing, Zhang, Xing, Xu, Yan, Li, Bin, He, Minging, Cai, Hongbo, Hao, Liang., Liu, Zhanjun, Zheng, Chunyang, Dai, Zhensheng, Fan, Zhengfeng, Qiao, Bin, Li, Fuquan, Jiang, Shaoen, Yu, M. Y., Zhu, Shaoping
A response to commenter Ke Lan's comment on our paper published in Nature Communications (2023)14:5782 by J. Yan et al
Externí odkaz:
http://arxiv.org/abs/2406.17555
We introduce latent intuitive physics, a transfer learning framework for physics simulation that can infer hidden properties of fluids from a single 3D video and simulate the observed fluid in novel scenes. Our key insight is to use latent features d
Externí odkaz:
http://arxiv.org/abs/2406.12769
Roadside perception is a key component in intelligent transportation systems. In this paper, we present a novel three-dimensional (3D) extended object tracking (EOT) method, which simultaneously estimates the object kinematics and extent state, in ro
Externí odkaz:
http://arxiv.org/abs/2404.17903
In this paper, we study the trajectory optimization of a cellular-connected unmanned aerial vehicle (UAV) which aims to sense the location of a target while maintaining satisfactory communication quality with the ground base stations (GBSs). In contr
Externí odkaz:
http://arxiv.org/abs/2404.10605
Multi-task learning (MTL) is a paradigm that simultaneously learns multiple tasks by sharing information at different levels, enhancing the performance of each individual task. While previous research has primarily focused on feature-level or paramet
Externí odkaz:
http://arxiv.org/abs/2404.00885
Autor:
Zhang, Beibei, Xiang, Tian, Mao, Chentao, Zheng, Yuhua, Li, Shuai, Niu, Haoyi, Xi, Xiangming, Bai, Wenyuan, Gao, Feng
Time-jerk optimal trajectory planning is crucial in advancing robotic arms' performance in dynamic tasks. Traditional methods rely on solving complex nonlinear programming problems, bringing significant delays in generating optimized trajectories. In
Externí odkaz:
http://arxiv.org/abs/2403.17353
Autor:
Zhao, Jingbo, Lu, Zhaoming, Zhang, J. Andrew, Li, Weicai, Xiong, Yifeng, Han, Zijun, Wen, Xiangming, Gu, Tao
This document contains the appendices for our paper titled ``Performance Bounds for Passive Sensing in Asynchronous ISAC Systems." The appendices include rigorous derivations of key formulas, detailed proofs of the theorems and propositions introduce
Externí odkaz:
http://arxiv.org/abs/2403.05793
Autor:
Gu, Xiangming, Zheng, Xiaosen, Pang, Tianyu, Du, Chao, Liu, Qian, Wang, Ye, Jiang, Jing, Lin, Min
A multimodal large language model (MLLM) agent can receive instructions, capture images, retrieve histories from memory, and decide which tools to use. Nonetheless, red-teaming efforts have revealed that adversarial images/prompts can jailbreak an ML
Externí odkaz:
http://arxiv.org/abs/2402.08567
For the linear inverse problem with sparsity constraints, the $l_0$ regularized problem is NP-hard, and existing approaches either utilize greedy algorithms to find almost-optimal solutions or to approximate the $l_0$ regularization with its convex c
Externí odkaz:
http://arxiv.org/abs/2402.08493