no code implementations • 9 Oct 2023 • Ruizhi Wang, Xiangtao Wang, Jie zhou, Thomas Lukasiewicz, Zhenghua Xu
In addition, word-level optimization based on numbers ignores the semantics of reports and medical images, and the generated reports often cannot achieve good performance.
no code implementations • 8 Sep 2023 • Xiangtao Wang, Ruizhi Wang, Jie zhou, Thomas Lukasiewicz, Zhenghua Xu
The proposed strategies effectively address limitations in applying masked modeling to medical images, tailored to capturing fine lesion details vital for segmentation tasks.
no code implementations • 15 Apr 2023 • Ruizhi Wang, Xiangtao Wang, Zhenghua Xu, Wenting Xu, Junyang Chen, Thomas Lukasiewicz
In clinical scenarios, multiple medical images with different views are usually generated at the same time, and they have high semantic consistency.
no code implementations • 27 Feb 2023 • Xiangtao Wang, Ruizhi Wang, Biao Tian, Jiaojiao Zhang, Shuo Zhang, Junyang Chen, Thomas Lukasiewicz, Zhenghua Xu
We leverage the masked patches selection strategy to choose masked patches with lesions to obtain more lesion representation information, and the adaptive masking strategy is utilized to help learn more mutual information and improve performance further.
no code implementations • 22 Feb 2023 • Hexiang Zhang, Zhenghua Xu, Dan Yao, Shuo Zhang, Junyang Chen, Thomas Lukasiewicz
Analysis of X-ray images is one of the main tools to diagnose breast cancer.
no code implementations • 16 Nov 2022 • Tommaso Salvatori, Yuhang Song, Yordan Yordanov, Beren Millidge, Zhenghua Xu, Lei Sha, Cornelius Emde, Rafal Bogacz, Thomas Lukasiewicz
Predictive coding networks are neuroscience-inspired models with roots in both Bayesian statistics and neuroscience.
no code implementations • 1 Nov 2022 • Zhenghua Xu, Changhong Deng, Qiuling Yang
Variable-speed pumped-storage (VSPS) has great potential in helping solve the frequency control problem caused by low inertia, owing to its remarkable flexibility beyond conventional fixed-speed one, to make better use of which, a primary frequency control strategy based on adaptive model predictive control (AMPC) is proposed in this paper for VSPS plant in power generation.
no code implementations • 14 Oct 2022 • Wenting Xu, Zhenghua Xu, Junyang Chen, Chang Qi, Thomas Lukasiewicz
In this article, we propose a hybrid reinforced medical report generation method with m-linear attention and repetition penalty mechanism (HReMRG-MR) to overcome these problems.
1 code implementation • 24 Jul 2022 • Zihang Xu, Zhenghua Xu, Shuo Zhang, Thomas Lukasiewicz
Unlike most existing semi-supervised learning methods, adversarial training based methods distinguish samples from different sources by learning the data distribution of the segmentation map, leading the segmenter to generate more accurate predictions.
no code implementations • NeurIPS 2021 • Tommaso Salvatori, Yuhang Song, Yujian Hong, Simon Frieder, Lei Sha, Zhenghua Xu, Rafal Bogacz, Thomas Lukasiewicz
We conclude by discussing the possible impact of this work in the neuroscience community, by showing that our model provides a plausible framework to study learning and retrieval of memories in the brain, as it closely mimics the behavior of the hippocampus as a memory index and generative model.
1 code implementation • CVPR 2021 • JianFeng Wang, Thomas Lukasiewicz, Xiaolin Hu, Jianfei Cai, Zhenghua Xu
Imbalanced datasets widely exist in practice and area great challenge for training deep neural models with agood generalization on infrequent classes.
Ranked #17 on Long-tail Learning on Places-LT
no code implementations • 8 Mar 2021 • Tommaso Salvatori, Yuhang Song, Thomas Lukasiewicz, Rafal Bogacz, Zhenghua Xu
Recent works prove that these methods can approximate BP up to a certain margin on multilayer perceptrons (MLPs), and asymptotically on any other complex model, and that zero-divergence inference learning (Z-IL), a variant of PC, is able to exactly implement BP on MLPs.
no code implementations • 5 Mar 2021 • Tommaso Salvatori, Yuhang Song, Thomas Lukasiewicz, Rafal Bogacz, Zhenghua Xu
Predictive coding networks (PCNs) are an influential model for information processing in the brain.
no code implementations • NeurIPS 2020 • Yuhang Song, Thomas Lukasiewicz, Zhenghua Xu, Rafal Bogacz
However, there are several gaps between BP and learning in biologically plausible neuronal networks of the brain (learning in the brain, or simply BL, for short), in particular, (1) it has been unclear to date, if BP can be implemented exactly via BL, (2) there is a lack of local plasticity in BP, i. e., weight updates require information that is not locally available, while BL utilizes only locally available information, and (3)~there is a lack of autonomy in BP, i. e., some external control over the neural network is required (e. g., switching between prediction and learning stages requires changes to dynamics and synaptic plasticity rules), while BL works fully autonomously.
no code implementations • 16 Nov 2020 • Wenting Xu, Chang Qi, Zhenghua Xu, Thomas Lukasiewicz
To reduce doctors' workload, deep-learning-based automatic medical report generation has recently attracted more and more research efforts, where attention mechanisms and reinforcement learning are integrated with the classic encoder-decoder architecture to enhance the performance of deep models.
no code implementations • 15 Nov 2020 • Chang Qi, Junyang Chen, Guizhi Xu, Zhenghua Xu, Thomas Lukasiewicz, Yang Liu
We first generate MRI images on limited datasets, then we trained three popular classification models to get the best model for tumor classification.
no code implementations • 15 Nov 2020 • Bo wang, Lei Wang, Junyang Chen, Zhenghua Xu, Thomas Lukasiewicz, Zhigang Fu
Non-local attention and feature learning by multi-scale methods are widely used to model network, which drives progress in medical image segmentation.
no code implementations • 15 Nov 2020 • Di Yuan, Junyang Chen, Zhenghua Xu, Thomas Lukasiewicz, Zhigang Fu, Guizhi Xu
However, U-Net is mainly engaged in segmentation, and the extracted features are also targeted at segmentation location information, and the input and output are different.
no code implementations • 2 Nov 2020 • Dan Zhao, Guizhi Xu, Zhenghua Xu, Thomas Lukasiewicz, Minmin Xue, Zhigang Fu
Computer-Aided Diagnosis and Treatment of Tumors is a hot topic of deep learning in recent years, which constitutes a series of medical tasks, such as detection of tumor markers, the outline of tumor leisures, subtypes and stages of tumors, prediction of therapeutic effect, and drug development.
4 code implementations • 2 Aug 2020 • Yixin Su, Rui Zhang, Sarah Erfani, Zhenghua Xu
To make the best out of feature interactions, we propose a graph neural network approach to effectively model them, together with a novel technique to automatically detect those feature interactions that are beneficial in terms of recommendation accuracy.
2 code implementations • 17 May 2019 • Yuhang Song, Andrzej Wojcicki, Thomas Lukasiewicz, Jianyi Wang, Abi Aryan, Zhenghua Xu, Mai Xu, Zihan Ding, Lianlong Wu
That is, there is not yet a general evaluation platform for research on multi-agent intelligence.
1 code implementation • 12 May 2019 • Yuhang Song, Jianyi Wang, Thomas Lukasiewicz, Zhenghua Xu, Shangtong Zhang, Andrzej Wojcicki, Mai Xu
Intrinsic rewards were introduced to simulate how human intelligence works; they are usually evaluated by intrinsically-motivated play, i. e., playing games without extrinsic rewards but evaluated with extrinsic rewards.
no code implementations • 30 Apr 2019 • Zehua Cheng, Yuxiang Wu, Zhenghua Xu, Thomas Lukasiewicz, Weiyang Wang
Region proposal mechanisms are essential for existing deep learning approaches to object detection in images.
Ranked #1 on Head Detection on Rebar Head
no code implementations • 6 Jan 2019 • Zehua Cheng, Zhenghua Xu
In order to save more communication bandwidth and preserve the accuracy on ring structure, which break the restrict as the node increase, we propose a new algorithm to measure the importance of gradients on large-scale cluster implementing ring all-reduce based on the size of the ratio of parameter calculation gradient to parameter value.
1 code implementation • 10 Nov 2018 • Yuhang Song, Jianyi Wang, Thomas Lukasiewicz, Zhenghua Xu, Mai Xu
However, HRL with multiple levels is usually needed in many real-world scenarios, whose ultimate goals are highly abstract, while their actions are very primitive.
Hierarchical Reinforcement Learning reinforcement-learning +1