no code implementations • 7 Oct 2024 • Shengyao Chen, Minghui He, Longyao Ran, Hongtao Li, Feng Xi, Sirui Tian, Zhong Liu
We aim to minimize the integrated sidelobe-to-mainlobe ratio (ISMR) of beampattern by the codesign of waveform and ARIS reflection coefficients.
no code implementations • 6 Apr 2024 • Tianle Pu, Changjun Fan, Mutian Shen, Yizhou Lu, Li Zeng, Zohar Nussinov, Chao Chen, Zhong Liu
The technique is originated from physics, but is very effective in enabling RL agents to explore to continuously improve the solutions during test.
no code implementations • 4 Feb 2024 • Zhengqiu Zhu, Yong Zhao, Bin Chen, Sihang Qiu, Kai Xu, Quanjun Yin, Jincai Huang, Zhong Liu, Fei-Yue Wang
The transition from CPS-based Industry 4. 0 to CPSS-based Industry 5. 0 brings new requirements and opportunities to current sensing approaches, especially in light of recent progress in Chatbots and Large Language Models (LLMs).
no code implementations • 20 Jan 2024 • Shengyao Chen, Qi Feng, Longyao Ran, Feng Xi, Zhong Liu
To maximize the output signal-to-interference-plus-noise ratio (SINR) of receive array, we formulate the codesign of transmit beamforming and RIS-assisted receive beamforming into a nonconvex constrained fractional programming problem, and then propose an alternating minimization-based algorithm to jointly optimize the transmitor beamfmer, receive beamformer and RIS reflection coefficients.
no code implementations • 13 Dec 2023 • Wenjie Wu, Changjun Fan, Jincai Huang, Zhong Liu, Junchi Yan
To the best of our knowledge, this is the first systematic review of ML-related methods for BPP.
1 code implementation • NeurIPS 2023 • Shuwei Shao, Zhongcai Pei, Xingming Wu, Zhong Liu, Weihai Chen, Zhengguo Li
To alleviate the possible error accumulation during the iterative process, we utilize a novel elastic target bin to replace the original target bin, the width of which is adjusted elastically based on the depth uncertainty.
Ranked #15 on Monocular Depth Estimation on KITTI Eigen split
no code implementations • 16 Aug 2023 • Bingxu Zhang, Changjun Fan, Shixuan Liu, Kuihua Huang, Xiang Zhao, Jincai Huang, Zhong Liu
Graph neural networks (GNNs) are effective machine learning models for many graph-related applications.
no code implementations • 8 Jul 2023 • Shixuan Liu, Changjun Fan, Kewei Cheng, Yunfei Wang, Peng Cui, Yizhou Sun, Zhong Liu
Heterogeneous Information Networks (HINs) are information networks with multiple types of nodes and edges.
2 code implementations • 21 Jun 2023 • Lin Xi, Weihai Chen, Xingming Wu, Zhong Liu, Zhengguo Li
Online unsupervised video object segmentation (UVOS) uses the previous frames as its input to automatically separate the primary object(s) from a streaming video without using any further manual annotation.
1 code implementation • 20 Feb 2023 • Zhong Liu, Ran Li, Shuwei Shao, Xingming Wu, Weihai Chen
In this work, we propose two novel ideas to improve self-supervised monocular depth estimation: 1) self-reference distillation and 2) disparity offset refinement.
1 code implementation • 16 Feb 2023 • Shuwei Shao, Zhongcai Pei, Weihai Chen, Ran Li, Zhong Liu, Zhengguo Li
Specifically, we use the depth estimates from the Transformer branch and the CNN branch as pseudo labels to teach each other.
Ranked #15 on Monocular Depth Estimation on KITTI Eigen split
no code implementations • 20 Nov 2022 • Jinyu Miao, Haosong Yue, Zhong Liu, Xingming Wu, Zaojun Fang, Guilin Yang
Local feature provides compact and invariant image representation for various visual tasks.
no code implementations • 30 May 2022 • Shuwei Shao, Zhongcai Pei, Weihai Chen, Xingming Wu, Zhong Liu, Zhengguo Li
Unsupervised monocular trained depth estimation models make use of adjacent frames as a supervisory signal during the training phase.
no code implementations • 13 May 2022 • Zhongyao Ma, Keyu Wu, Zhong Liu
Finally, through simulation experiments in typical scenarios, this paper studies and compares the air defense capabilities of the system in two different modes with and without coordination, and verifies the superiority of the multi-ship cooperative air defense model in reducing the probability of missile penetration; Further, the ability changes of the defense system under different parameters such as missile speed, speed, angle, ship interception rate, range, and number of fire units are studied, and the weak points of the defense formation, defense range settings, and interception settings are obtained.
1 code implementation • 6 Apr 2022 • Lin Xi, Weihai Chen, Xingming Wu, Zhong Liu, Zhengguo Li
Unsupervised video object segmentation (UVOS) aims at automatically separating the primary foreground object(s) from the background in a video sequence.
no code implementations • 18 Jan 2022 • Yan Zhao, Lingjun Zhao, Zhong Liu, Dewen Hu, Gangyao Kuang, Li Liu
Aircraft detection in Synthetic Aperture Radar (SAR) imagery is a challenging task in SAR Automatic Target Recognition (SAR ATR) areas due to aircraft's extremely discrete appearance, obvious intraclass variation, small size and serious background's interference.
no code implementations • 25 Dec 2021 • Ziyang Liu, Zhengguo Li, Xingming Wu, Zhong Liu, Weihai Chen
The proposed method, named DSRGAN, includes a well designed detail extraction algorithm to capture the most important high frequency information from images.
no code implementations • 7 Dec 2021 • Xingxing Liang, Yang Ma, Yanghe Feng, Zhong Liu
In addition, by analyzing the heatmap of priority changes at various locations in the priority memory during training, we find that memory size and rollout length can have a significant impact on the distribution of trajectory priorities and, hence, on the performance of the algorithm.
no code implementations • 16 Nov 2021 • Shuwei Shao, Ran Li, Zhongcai Pei, Zhong Liu, Weihai Chen, Wentao Zhu, Xingming Wu, Baochang Zhang
In this work, we investigate into the phenomenon and propose to integrate the strengths of multiple weak depth predictor to build a comprehensive and accurate depth predictor, which is critical for many real-world applications, e. g., 3D reconstruction.
1 code implementation • Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) 2021 • Mingjie Li, Wenjia Cai, Rui Liu, Yuetian Weng, Xiaoyun Zhao, Cong Wang, Xin Chen, Zhong Liu, Caineng Pan, Mengke Li, Yizhi Liu, Flora D Salim, Karin Verspoor, Xiaodan Liang, Xiaojun Chang
Researchers have explored advanced methods from computer vision and natural language processing to incorporate medical domain knowledge for the generation of readable medical reports.
no code implementations • 18 Mar 2021 • Yuxin Tian, Jinyu Miao, Xingming Wu, Haosong Yue, Zhong Liu, Weihai Chen
In this paper, we address the challenges of place recognition due to dynamics and confusable patterns by proposing a discriminative and semantic feature selection network, dubbed as DSFeat.
no code implementations • 14 Oct 2020 • Huizhang Yang, Mingliang Tao, Shengyao Chen, Feng Xi, Zhong Liu
Based on the low rank model, we show that two methods, i. e., principle component analysis and its robust variant, can be adopted to efficiently mitigate the artefact via processing in image domain.
no code implementations • 22 Jul 2019 • Chengyu Guo, Jingyun Liang, Geng Zhan, Zhong Liu, Matti Pietikäinen, Li Liu
It is computationally efficient and only marginally increases the cost of computing LBPTOP, yet is extremely effective for ME recognition.
1 code implementation • 24 May 2019 • Changjun Fan, Li Zeng, Yuhui Ding, Muhao Chen, Yizhou Sun, Zhong Liu
By training on small-scale networks, the learned model is capable of assigning relative BC scores to nodes for any unseen networks, and thus identifying the highly-ranked nodes.
no code implementations • 24 Dec 2018 • Xingxing Liang, Qi. Wang, Yanghe Feng, Zhong Liu, Jincai Huang
Recent breakthroughs in Go play and strategic games have witnessed the great potential of reinforcement learning in intelligently scheduling in uncertain environment, but some bottlenecks are also encountered when we generalize this paradigm to universal complex tasks.