no code implementations • 16 Apr 2024 • Fan Zhang, Jinfeng Chen, Yu Hu, Zhiqiang Gao, Ge Lv, Qin Lin
On the other hand, machine learning benefits from an additional assurance layer provided by the ESO, as any imperfections in the machine learning model can be compensated for by the ESO.
no code implementations • 15 Apr 2024 • Zou Zhen, Yu Hu, Zhao Feng
Recent studies have witnessed the effectiveness and efficiency of Mamba for perceiving global and local information based on its exploiting local correlation among patches, however, rarely attempts have been explored to extend it with frequency analysis for image deraining, limiting its ability to perceive global degradation that is relevant to frequency modeling (e. g. Fourier transform).
1 code implementation • 26 Jul 2023 • Jin Wang, Yu Hu, Lirong Xiang, Gota Morota, Samantha A. Brooks, Carissa L. Wickens, Emily K. Miller-Cushon, Haipeng Yu
Moreover, the rapid expansion of precision livestock farming is creating a growing need to educate and train animal science students in CV.
1 code implementation • CVPR 2023 • Shun Lu, Yu Hu, Longxing Yang, Zihao Sun, Jilin Mei, Jianchao Tan, Chengru Song
Our method only requires negligible computation cost for optimizing the sampling distributions of path and data, but achieves lower gradient variance during supernet training and better generalization performance for the supernet, resulting in a more consistent NAS.
no code implementations • 24 Feb 2023 • Baolin Peng, Michel Galley, Pengcheng He, Hao Cheng, Yujia Xie, Yu Hu, Qiuyuan Huang, Lars Liden, Zhou Yu, Weizhu Chen, Jianfeng Gao
Large language models (LLMs), such as ChatGPT, are able to generate human-like, fluent responses for many downstream tasks, e. g., task-oriented dialog and question answering.
no code implementations • 17 Feb 2023 • Jilin Mei, Junbao Zhou, Yu Hu
Thus, we propose a few-shot 3D LiDAR semantic segmentation method that predicts both novel classes and base classes simultaneously.
Autonomous Driving Generalized Few-Shot Semantic Segmentation +4
no code implementations • 3 Feb 2023 • Hongmin Cai, Fei Qi, Junyu Li, Yu Hu, Yue Zhang, Yiu-ming Cheung, Bin Hu
Conventional clustering methods based on pairwise affinity usually suffer from the concentration effect while processing huge dimensional features yet low sample sizes data, resulting in inaccuracy to encode the sample proximity and suboptimal performance in clustering.
no code implementations • ICCV 2023 • Zihao Sun, Yu Sun, Longxing Yang, Shun Lu, Jilin Mei, Wenxiao Zhao, Yu Hu
Neural Architecture Search (NAS) aims to automatically find optimal neural network architectures in an efficient way.
1 code implementation • 31 Dec 2022 • Zixiang Luo, Kaining Peng, Zhichao Liang, Shengyuan Cai, Chenyu Xu, Dan Li, Yu Hu, Changsong Zhou, Quanying Liu
Effective connectivity (EC), indicative of the causal interactions between brain regions, is fundamental to understanding information processing in the brain.
no code implementations • 4 Dec 2022 • Yirong Zhou, Chen Qian, Jiayu Li, Zi Wang, Yu Hu, Biao Qu, Liuhong Zhu, Jianjun Zhou, Taishan Kang, Jianzhong Lin, Qing Hong, Jiyang Dong, Di Guo, Xiaobo Qu
Efficient collaboration between engineers and radiologists is important for image reconstruction algorithm development and image quality evaluation in magnetic resonance imaging (MRI).
1 code implementation • CVPR 2023 • Xinjiang Wang, Zeyu Liu, Yu Hu, Wei Xi, Wenxian Yu, Danping Zou
We introduce a lightweight network to improve descriptors of keypoints within the same image.
no code implementations • 25 Aug 2022 • Jinfeng Chen, Zhiqiang Gao, Yu Hu, Sally Shao
A general model-based extended state observer (GMB-ESO) is proposed for single-input single-output linear time-invariant systems with a given state space model, where the total disturbance, a lump sum of model uncertainties and external disturbances, is defined as an extended state in the same manner as in the original formulation of ESO.
1 code implementation • International Conference on Machine Learning 2022 • Zihao Sun, Yu Hu, Shun Lu, Longxing Yang, Jilin Mei, Yinhe Han, Xiaowei Li
We utilize the attention weights to represent the importance of the relevant operations for the micro search or the importance of the relevant blocks for the macro search.
no code implementations • 18 Dec 2021 • Yu Hu, Miguel Armada, Maria Jesus Sanchez
The result shows that under the current empirical estimation of the battery cost and lifetime, BESS is not feasible for energy arbitrage in most of the European electricity markets.
1 code implementation • BMVC 2021 • Shun Lu, Yu Hu, Longxing Yang, Zihao Sun, Jilin Mei, Yiming Zeng, Xiaowei Li
Differentiable Neural Architecture Search (DARTS) recently attracts a lot of research attention because of its high efficiency.
Ranked #9 on Neural Architecture Search on CIFAR-100
1 code implementation • 22 Jul 2021 • Xingmei Lou, Yu Hu, XiaoDong Li
We are interested in the problem of learning the directed acyclic graph (DAG) when data are generated from a linear structural equation model (SEM) and the causal structure can be characterized by a polytree.
no code implementations • 9 Jun 2021 • Ling Li, Yu Hu
Synchrotron radiation sources are widely used in various fields, among which computed tomography (CT) is one of the most important.
no code implementations • 25 Apr 2021 • Wentao Chen, Hailong Qiu, Jian Zhuang, Chutong Zhang, Yu Hu, Qing Lu, Tianchen Wang, Yiyu Shi, Meiping Huang, Xiaowe Xu
Deep neural networks (DNNs) have demonstrated their great potential in recent years, exceeding the per-formance of human experts in a wide range of applications.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +5
no code implementations • 7 Feb 2021 • Jie Li, Yu Hu
In this paper, we put forward a novel density-oriented PointNet (DPointNet) for 3D object detection in point clouds, in which the density of points increases layer by layer.
no code implementations • 12 Jan 2021 • Zhengqing Zhou, Zhiheng Zhao, Shuyu Shi, Jianghua Wu, Dianjie Li, Jianwei Li, Jingpeng Zhang, Ke Gui, Yu Zhang, Heng Mei, Yu Hu, Qi Ouyang, Fangting Li
Integrating theoretical results with clinical COVID-19 patients' data, we classified the COVID-19 development processes into three typical modes of immune responses, correlated with the clinical classification of mild & moderate, severe and critical patients.
no code implementations • 1 Jan 2021 • Tianlong Chen, Yu Cheng, Zhe Gan, Yu Hu, Zhangyang Wang, Jingjing Liu
Adversarial training is an effective method to combat adversarial attacks in order to create robust neural networks.
no code implementations • 28 Dec 2020 • Hang Chen, Jun Du, Yu Hu, Li-Rong Dai, Chin-Hui Lee, Bao-Cai Yin
In this paper, we propose a novel deep learning architecture to improving word-level lip-reading.
1 code implementation • 9 Dec 2020 • Run-Ze Wang, Zhen-Hua Ling, Jing-Bo Zhou, Yu Hu
The dynamic schema-state and SQL-state representations are then utilized to decode the SQL query corresponding to current utterance.
no code implementations • 21 Sep 2020 • Hang Chen, Jun Du, Yu Hu, Li-Rong Dai, Bao-Cai Yin, Chin-Hui Lee
We first extract visual embedding from lip frames using a pre-trained phone or articulation place recognizer for visual-only EASE (VEASE).
no code implementations • 11 Sep 2020 • Jie Li, Yu Hu
We present an improved version of PointRCNN for 3D object detection, in which a multi-branch backbone network is adopted to handle the non-uniform density of point clouds.
no code implementations • 28 Jun 2020 • Yu Hu, David Soler Soneira, María Jesús Sánchez
The concept of "potentially profitable utilization time" is proposed and introduced to identify and evaluate future potential grid applications for battery systems.
1 code implementation • CVPR 2020 • Beibei Jin, Yu Hu, Qiankun Tang, Jingyu Niu, Zhiping Shi, Yinhe Han, Xiaowei Li
Inspired by the frequency band decomposition characteristic of Human Vision System (HVS), we propose a video prediction network based on multi-level wavelet analysis to deal with spatial and temporal information in a unified manner.
Ranked #1 on Video Prediction on KTH (PSNR metric)
no code implementations • 9 Aug 2019 • Qiankun Tang, Shice Liu, Jie Li, Yu Hu
We introduce a novel single-shot object detector to ease the imbalance of foreground-background class by suppressing the easy negatives while increasing the positives.
no code implementations • 10 May 2019 • Hong Peng, Yu Hu, Jiazhou Chen, Hai-Yan Wang, Yang Li, Hongmin Cai
The performance of most the clustering methods hinges on the used pairwise affinity, which is usually denoted by a similarity matrix.
1 code implementation • NeurIPS 2018 • Shice Liu, Yu Hu, Yiming Zeng, Qiankun Tang, Beibei Jin, Yinhe Han, Xiaowei Li
Semantic scene completion predicts volumetric occupancy and object category of a 3D scene, which helps intelligent agents to understand and interact with the surroundings.
1 code implementation • IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2018 • Beibei Jin, Yu Hu, Yiming Zeng, Qiankun Tang, Shice Liu, Jing Ye
For the KTH dataset, the VarNet outperforms the state-of-the-art works up to 11. 9% on PSNR and 9. 5% on SSIM.
Ranked #1 on Video Prediction on KTH (Cond metric)
no code implementations • CVPR 2018 • Xiaowei Xu, Qing Lu, Yu Hu, Lin Yang, Sharon Hu, Danny Chen, Yiyu Shi
Unlike existing litera- ture on quantization which primarily targets memory and computation complexity reduction, we apply quan- tization as a method to reduce over tting in FCNs for better accuracy.
no code implementations • 13 Nov 2016 • Quan Liu, Hui Jiang, Zhen-Hua Ling, Xiaodan Zhu, Si Wei, Yu Hu
The PDP task we investigate in this paper is a complex coreference resolution task which requires the utilization of commonsense knowledge.
Ranked #63 on Coreference Resolution on Winograd Schema Challenge
no code implementations • 24 Mar 2016 • Quan Liu, Hui Jiang, Andrew Evdokimov, Zhen-Hua Ling, Xiaodan Zhu, Si Wei, Yu Hu
We propose to use neural networks to model association between any two events in a domain.
Ranked #11 on Natural Language Understanding on PDP60
Natural Language Inference Natural Language Understanding +2
no code implementations • 24 Mar 2016 • Quan Liu, Zhen-Hua Ling, Hui Jiang, Yu Hu
The model proposed in this paper paper jointly optimizes word vectors and the POS relevance matrices.
no code implementations • 28 Dec 2015 • Shiliang Zhang, Cong Liu, Hui Jiang, Si Wei, Li-Rong Dai, Yu Hu
In this paper, we propose a novel neural network structure, namely \emph{feedforward sequential memory networks (FSMN)}, to model long-term dependency in time series without using recurrent feedback.