no code implementations • 7 Jul 2023 • Jia-Qi Zhang, Hao-Bin Duan, Jun-Long Chen, Ariel Shamir, Miao Wang
By utilizing the lane features in the Hough parameter space, the network learns dynamic convolution kernel parameters corresponding to each lane, allowing the Dynamic Convolution Module to effectively differentiate between lane features.
no code implementations • 2 Sep 2020 • Lufan Chang, Wenjing Zhuang, Richeng Wu, Sai Feng, Hao liu, Jing Yu, Jia Ding, Ziteng Wang, Jia-Qi Zhang
Our platform is consists of a radiomics module and a deep learning module.
no code implementations • 29 Mar 2020 • Senlin Yang, Zhengfang Wang, Jing Wang, Anthony G. Cohn, Jia-Qi Zhang, Peng Jiang, Qingmei Sui
This research proposes a Ground Penetrating Radar (GPR) data processing method for non-destructive detection of tunnel lining internal defects, called defect segmentation.
no code implementations • 24 Mar 2020 • Min Shi, Jia-Qi Zhang, Shu-Yu Chen, Lin Gao, Yu-Kun Lai, Fang-Lue Zhang
The color transform network takes the target line art images as well as the line art and color images of one or more reference images as input, and generates corresponding target color images.
no code implementations • 1 Mar 2020 • Xingyu Sha, Jia-Qi Zhang, Keyou You, Kaiqing Zhang, Tamer Başar
This paper proposes a \emph{fully asynchronous} scheme for the policy evaluation problem of distributed reinforcement learning (DisRL) over directed peer-to-peer networks.
no code implementations • 12 Feb 2019 • Zhenyi Liu, Minghao Shen, Jia-Qi Zhang, Shuangting Liu, Henryk Blasinski, Trisha Lian, Brian Wandell
We describe an open-source simulator that creates sensor irradiance and sensor images of typical automotive scenes in urban settings.
no code implementations • 1 Nov 2018 • Shuangting Liu, Jia-Qi Zhang, Yuxin Chen, Yifan Liu, Zengchang Qin, Tao Wan
Semantic segmentation is one of the basic topics in computer vision, it aims to assign semantic labels to every pixel of an image.
no code implementations • NeurIPS 2013 • Ziteng Wang, Kai Fan, Jia-Qi Zhang, Li-Wei Wang
Outputting the summary runs in time $O(n^{1+\frac{d}{2d+K}})$, and the evaluation algorithm for answering a query runs in time $\tilde O (n^{\frac{d+2+\frac{2d}{K}}{2d+K}} )$.