no code implementations • 11 Mar 2024 • Zijian Zhou, Miaojing Shi, Meng Wei, Oluwatosin Alabi, Zijie Yue, Tom Vercauteren
Finally, to better reflect the clinical significant and insignificant errors that radiologists would normally assign in the report, we introduce a novel clinical quality reinforcement learning strategy.
1 code implementation • 27 Nov 2023 • Zijian Zhou, Miaojing Shi, Holger Caesar
Panoptic Scene Graph Generation (PSG) aims at achieving a comprehensive image understanding by simultaneously segmenting objects and predicting relations among objects.
Ranked #1 on Panoptic Scene Graph Generation on PSG Dataset
no code implementations • 13 Nov 2023 • Yitong Sun, Zijian Zhou, Cyriel Diels, Ali Asadipour
Despite the enhanced realism and immersion provided by VR headsets, users frequently encounter adverse effects such as digital eye strain (DES), dry eye, and potential long-term visual impairment due to excessive eye stimulation from VR displays and pressure from the mask.
no code implementations • 29 Sep 2023 • Junchao Chen, Jin Song, Zijian Zhou, Zhenya Yan
In this paper, we study data-driven localized wave solutions and parameter discovery in the massive Thirring (MT) model via the deep learning in the framework of physics-informed neural networks (PINNs) algorithm.
1 code implementation • ICCV 2023 • Zijian Zhou, Miaojing Shi, Holger Caesar
Existing unbiased methods tackle the long-tail problem by data/loss rebalancing to favor low-frequency relations.
Ranked #2 on Panoptic Scene Graph Generation on PSG Dataset
1 code implementation • 1 Dec 2022 • Zijian Zhou, Xinyi Xu, Rachael Hwee Ling Sim, Chuan Sheng Foo, Kian Hsiang Low
We observe that the fairness guarantees of exact SVs are too restrictive for SV estimates.
no code implementations • 5 Sep 2022 • Zijian Zhou, Lifeng Lin, Bingli Jiao
As has been known, the Nyquist first condition promises no intersymbol interference (ISI) as derived in the frequency domain.
no code implementations • 28 Dec 2021 • Zijian Zhou, Li Wang, Zhenya Yan
In this paper, we investigate the forward problems on the data-driven rational solitons for the (2+1)-dimensional KP-I equation and spin-nonlinear Schr\"odinger (spin-NLS) equation via the deep neural networks leaning.
no code implementations • 18 Nov 2021 • Zijian Zhou, Li Wang, Weifang Weng, Zhenya Yan
We introduce a deep neural network learning scheme to learn the B\"acklund transforms (BTs) of soliton evolution equations and an enhanced deep learning scheme for data-driven soliton equation discovery based on the known BTs, respectively.
no code implementations • 30 Apr 2021 • Zijian Zhou, Zhenya Yan
The third-order nonlinear Schrodinger equation (alias the Hirota equation) is investigated via deep leaning neural networks, which describes the strongly dispersive ion-acoustic wave in plasma and the wave propagation of ultrashort light pulses in optical fibers, as well as broader-banded waves on deep water.
2 code implementations • 1 Mar 2021 • Haoran You, Zhihan Lu, Zijian Zhou, Yonggan Fu, Yingyan Lin
Experiments on various GCN models and datasets consistently validate our GEB finding and the effectiveness of our GEBT, e. g., our GEBT achieves up to 80. 2% ~ 85. 6% and 84. 6% ~ 87. 5% savings of GCN training and inference costs while offering a comparable or even better accuracy as compared to state-of-the-art methods.
6 code implementations • ICLR 2021 • Xinyue Chen, Che Wang, Zijian Zhou, Keith Ross
Using a high Update-To-Data (UTD) ratio, model-based methods have recently achieved much higher sample efficiency than previous model-free methods for continuous-action DRL benchmarks.
no code implementations • 3 Oct 2020 • Yilin Xiong, Zijian Zhou, Yuhao Dou, Zhizhong Su
Significant progress has been made in facial landmark detection with the development of Convolutional Neural Networks.
1 code implementation • NeurIPS 2020 • Xinyue Chen, Zijian Zhou, Zheng Wang, Che Wang, Yanqiu Wu, Keith Ross
There has recently been a surge in research in batch Deep Reinforcement Learning (DRL), which aims for learning a high-performing policy from a given dataset without additional interactions with the environment.