Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Chaoyun, Zhang"'
In this paper, we consider the Click-Through-Rate (CTR) prediction problem. Factorization Machines and their variants consider pair-wise feature interactions, but normally we won't do high-order feature interactions using FM due to high time complexi
Externí odkaz:
http://arxiv.org/abs/2012.10820
Publikováno v:
IEEE Access, Vol 8, Pp 191138-191151 (2020)
Understanding driver activity is vital for in-vehicle systems that aim to reduce the incidence of car accidents rooted in cognitive distraction. Automating real-time behavior recognition while ensuring actions classification with high accuracy is how
Externí odkaz:
https://doaj.org/article/ab28758f8c92475cb5716345fbef3fb5
Publikováno v:
IEEE Access, Vol 7, Pp 40757-40770 (2019)
Multi-task learning (MTL) is a machine learning method to share knowledge for multiple related machine learning tasks via learning those tasks jointly. It has been shown to be capable of effectively improving the generalization capability of each sin
Externí odkaz:
https://doaj.org/article/9a37a48b3c6c416e8f6421096c8ffff7
Autor:
Chaoyun Zhang, Xiaoling Peng, Jing Li, Tristan Ellis, Qiong Wu, Jingcai Xu, Bo Hong, Xinqing Wang, Hongliang Ge
Publikováno v:
Journal of Superconductivity and Novel Magnetism. 36:923-929
Publikováno v:
IEEE Transactions on Network Science and Engineering. :1-11
Autor:
Qian Wang, Wenhua Zang, Li Han, Lei Yang, Songshan Ye, Jingfeng Ouyang, Chaoyun Zhang, Yuefeng Bi, Cuiyue Zhang, Hua Bian
Publikováno v:
Chinese Medicine, Vol 13, Iss 1, Pp 1-14 (2018)
Abstract Background Systemic sclerosis (SSc) is an autoimmune disease characterized by fibrosis of the skin and internal organs. So far, no Western medicine treatment can completely inhibit or reverse the progress of SSc, while at the same time, our
Externí odkaz:
https://doaj.org/article/d357a48ee34a4feb9ac0e2b1dd404cc8
Publikováno v:
Anti-Corrosion Methods and Materials.
Purpose This study aims to solve the problems of ambiguous localization, large calculation, poor real-time and limited applicability of bolt thread defect detection. Design/methodology/approach First, the acquired ultrasound image is used to acquire
Publikováno v:
Zhang, C, Costa-Pérez, X & Patras, P 2022, ' Adversarial Attacks Against Deep Learning-based Network Intrusion Detection Systems and Defense Mechanisms ', IEEE/ACM Transactions on Networking, vol. 30, no. 3, pp. 1294-1311 . https://doi.org/10.1109/TNET.2021.3137084
Neural networks (NNs) are increasingly popular in developing NIDS, yet can prove vulnerable to adversarial examples. Through these, attackers that may be oblivious to the precise mechanics of the targeted NIDS add subtle perturbations to malicious tr
Autor:
Ge Fan, Chaoyun Zhang, Junyang Chen, Baopu Li, Zenglin Xu, Yingjie Li, Luyu Peng, Zhiguo Gong
Publikováno v:
2022 IEEE 38th International Conference on Data Engineering (ICDE).
Publikováno v:
IEEE Access, Vol 8, Pp 191138-191151 (2020)
Zhang, C, Li, R, Kim, W, Yoon, D & Patras, P 2020, ' Driver Behavior Recognition via Interwoven Deep Convolutional Neural Nets With Multi-Stream Inputs ', IEEE Access, vol. 8, pp. 191138-191151 . https://doi.org/10.1109/ACCESS.2020.3032344
Zhang, C, Li, R, Kim, W, Yoon, D & Patras, P 2020, ' Driver Behavior Recognition via Interwoven Deep Convolutional Neural Nets With Multi-Stream Inputs ', IEEE Access, vol. 8, pp. 191138-191151 . https://doi.org/10.1109/ACCESS.2020.3032344
Understanding driver activity is vital for in-vehicle systems that aim to reduce the incidence of car accidents rooted in cognitive distraction. Automating real-time behavior recognition while ensuring actions classification with high accuracy is how