Zobrazeno 1 - 10
of 725
pro vyhledávání: '"ZHOU Ziqi"'
Publikováno v:
Xibei zhiwu xuebao, Vol 44, Iss 7, Pp 1122-1128 (2024)
Abstract [Objective] Sagittaria trifolia is an important horticultural and cash crop in China. Identification of genome size and analysis of karyotype are essential for genome research and molecular genetics of S. trifolia. Currently, the genome si
Externí odkaz:
https://doaj.org/article/678c1113bfe642d9bc4f72bc696b7391
Despite being prominent and ubiquitous, message-based interaction is limited in nonverbally conveying emotions. Besides emoticons or stickers, messaging users continue seeking richer options for affective communication. Recent research explored using
Externí odkaz:
http://arxiv.org/abs/2408.06294
The success of deep face recognition (FR) systems has raised serious privacy concerns due to their ability to enable unauthorized tracking of users in the digital world. Previous studies proposed introducing imperceptible adversarial noises into face
Externí odkaz:
http://arxiv.org/abs/2408.01428
Autor:
Zhang, Hangtao, Zhu, Chenyu, Wang, Xianlong, Zhou, Ziqi, Wang, Yichen, Xue, Lulu, Li, Minghui, Hu, Shengshan, Zhang, Leo Yu
Embodied artificial intelligence (AI) represents an artificial intelligence system that interacts with the physical world through sensors and actuators, seamlessly integrating perception and action. This design enables AI to learn from and operate wi
Externí odkaz:
http://arxiv.org/abs/2407.20242
Autor:
Zhou Ziqi
Publikováno v:
SHS Web of Conferences, Vol 163, p 01023 (2023)
Regional integration is an important measure to promote the development of China’s regional economy. Analyzing regional economies through statistical methods and studying the causes of regional economic differences can provide effective analysis an
Externí odkaz:
https://doaj.org/article/74115eb3c392481bb04ead17e7996106
Autor:
Wang, Xianlong, Hu, Shengshan, Zhang, Yechao, Zhou, Ziqi, Zhang, Leo Yu, Xu, Peng, Wan, Wei, Jin, Hai
Clean-label indiscriminate poisoning attacks add invisible perturbations to correctly labeled training images, thus dramatically reducing the generalization capability of the victim models. Recently, some defense mechanisms have been proposed such as
Externí odkaz:
http://arxiv.org/abs/2406.15093
One of the key challenges in current Reinforcement Learning (RL)-based Automated Driving (AD) agents is achieving flexible, precise, and human-like behavior cost-effectively. This paper introduces an innovative approach utilizing Large Language Model
Externí odkaz:
http://arxiv.org/abs/2405.04135
Autor:
Zhang, Hangtao, Hu, Shengshan, Wang, Yichen, Zhang, Leo Yu, Zhou, Ziqi, Wang, Xianlong, Zhang, Yanjun, Chen, Chao
Object detection tasks, crucial in safety-critical systems like autonomous driving, focus on pinpointing object locations. These detectors are known to be susceptible to backdoor attacks. However, existing backdoor techniques have primarily been adap
Externí odkaz:
http://arxiv.org/abs/2404.11357
Multimodal Sentiment Analysis (MSA) endeavors to understand human sentiment by leveraging language, visual, and acoustic modalities. Despite the remarkable performance exhibited by previous MSA approaches, the presence of inherent multimodal heteroge
Externí odkaz:
http://arxiv.org/abs/2404.04545
Autor:
Zhou, Ziqi, Li, Minghui, Liu, Wei, Hu, Shengshan, Zhang, Yechao, Wan, Wei, Xue, Lulu, Zhang, Leo Yu, Yao, Dezhong, Jin, Hai
With the evolution of self-supervised learning, the pre-training paradigm has emerged as a predominant solution within the deep learning landscape. Model providers furnish pre-trained encoders designed to function as versatile feature extractors, ena
Externí odkaz:
http://arxiv.org/abs/2403.10801