no code implementations • 24 Aug 2023 • Jakob Engel, Kiran Somasundaram, Michael Goesele, Albert Sun, Alexander Gamino, Andrew Turner, Arjang Talattof, Arnie Yuan, Bilal Souti, Brighid Meredith, Cheng Peng, Chris Sweeney, Cole Wilson, Dan Barnes, Daniel DeTone, David Caruso, Derek Valleroy, Dinesh Ginjupalli, Duncan Frost, Edward Miller, Elias Mueggler, Evgeniy Oleinik, Fan Zhang, Guruprasad Somasundaram, Gustavo Solaira, Harry Lanaras, Henry Howard-Jenkins, Huixuan Tang, Hyo Jin Kim, Jaime Rivera, Ji Luo, Jing Dong, Julian Straub, Kevin Bailey, Kevin Eckenhoff, Lingni Ma, Luis Pesqueira, Mark Schwesinger, Maurizio Monge, Nan Yang, Nick Charron, Nikhil Raina, Omkar Parkhi, Peter Borschowa, Pierre Moulon, Prince Gupta, Raul Mur-Artal, Robbie Pennington, Sachin Kulkarni, Sagar Miglani, Santosh Gondi, Saransh Solanki, Sean Diener, Shangyi Cheng, Simon Green, Steve Saarinen, Suvam Patra, Tassos Mourikis, Thomas Whelan, Tripti Singh, Vasileios Balntas, Vijay Baiyya, Wilson Dreewes, Xiaqing Pan, Yang Lou, Yipu Zhao, Yusuf Mansour, Yuyang Zou, Zhaoyang Lv, Zijian Wang, Mingfei Yan, Carl Ren, Renzo De Nardi, Richard Newcombe
Egocentric, multi-modal data as available on future augmented reality (AR) devices provides unique challenges and opportunities for machine perception.
no code implementations • 30 Jul 2023 • Yang Lou, Qun Song, Qian Xu, Rui Tan, JianPing Wang
Multi-modal fusion has shown initial promising results for object detection of autonomous driving perception.
no code implementations • 13 May 2023 • Chengpei Wu, Yang Lou, Lin Wang, Junli Li, Xiang Li, Guanrong Chen
This paper addresses the robustness of a network to sustain its connectivity and controllability against malicious attacks.
no code implementations • 25 Aug 2022 • Chengpei Wu, Yang Lou, Ruizi Wu, Wenwen Liu, Junli Li
In this paper, we investigate the performance of CNN-based approaches for connectivity and controllability robustness prediction, when partial network information is missing, namely the adjacency matrix is incomplete.
no code implementations • 20 Mar 2022 • Yang Lou, Ruizi Wu, Junli Li, Lin Wang, Xiang Li, Guanrong Chen
Extensive experimental studies on both synthetic and real-world networks, both directed and undirected, demonstrate that 1) the proposed LFR-CNN performs better than other two state-of-the-art prediction methods, with significantly lower prediction errors; 2) LFR-CNN is insensitive to the variation of the network size, which significantly extends its applicability; 3) although LFR-CNN needs more time to perform feature learning, it can achieve accurate prediction faster than attack simulations; 4) LFR-CNN not only can accurately predict network robustness, but also provides a good indicator for connectivity robustness, better than the classical spectral measures.
1 code implementation • 6 Aug 2021 • Jindi Zhang, Yang Lou, JianPing Wang, Kui Wu, Kejie Lu, Xiaohua Jia
In this paper, we investigate the impact of two primary types of adversarial attacks, perturbation attacks and patch attacks, on the driving safety of vision-based autonomous vehicles rather than the detection precision of deep learning models.
no code implementations • 3 Jan 2021 • Dinghua Shi, Zhifeng Chen, Xiang Sun, Qinghua Chen, Chuang Ma, Yang Lou, Guanrong Chen
Complex networks contain complete subgraphs such as nodes, edges, triangles, etc., referred to as simplices and cliques of different orders.
no code implementations • 26 Aug 2019 • Yang Lou, Yaodong He, Lin Wang, Guanrong Chen
Under the new framework, a fairly large number of training data generated by simulations are used to train a convolutional neural network for predicting the controllability robustness according to the input network-adjacency matrices, without performing conventional attack simulations.
no code implementations • 14 May 2019 • Yujia Chen, Yang Lou, Kun Wang, Matthew A. Kupinski, Mark A. Anastasio
In this work, a sparsity-driven observer (SDO) that can be employed to optimize hardware by use of a stochastic object model describing object sparsity is described and investigated.
no code implementations • 16 Mar 2019 • Yang Lou, Shiu Yin Yuen, Guanrong Chen, Xin Zhang
The entire on-line search history of cNrGA is stored in a binary space partitioning (BSP) tree, which is effective for performing local search.
no code implementations • 20 May 2016 • Yang Lou, Guanrong Chen, Zhengping Fan, Luna Xiang
Naming game, on the other hand, is a social communication model that simulates the process of learning a name of an object within a community of humans, where the individuals can generally reach global consensus asymptotically through iterative pair-wise conversations.
no code implementations • 28 Dec 2015 • Yang Lou, Guanrong Chen, Jianwei Hu
Naming game simulates the process of naming an object by a single word, in which a population of communicating agents can reach global consensus asymptotically through iteratively pair-wise conversations.