no code implementations • 6 Feb 2022 • Sitong Liu, Zhichao Lian, Siqi Gu, Liang Xiao
Although the deepfake detection based on convolutional neural network has achieved good results, the detection results show that these detectors show obvious performance degradation when the input images undergo some common transformations (like resizing, blurring), which indicates that the generalization ability of the detector is insufficient.
no code implementations • 22 Oct 2021 • Jianjun Liu, Zebin Wu, Liang Xiao, Xiao-Jun Wu
Inspired by the specific properties of model, we make the first attempt to design a model inspired deep network for HSI super-resolution in an unsupervised manner.
1 code implementation • 16 May 2021 • Yu Shen, Sijie Zhu, Taojiannan Yang, Chen Chen, Delu Pan, Jianyu Chen, Liang Xiao, Qian Du
With a pair of pre- and post-disaster satellite images, building damage assessment aims at predicting the extent of damage to buildings.
Ranked #1 on
2D Semantic Segmentation
on xBD
1 code implementation • 9 May 2021 • Jiaolong Xu, Liang Xiao, Dawei Zhao, Yiming Nie, Bin Dai
The experimental results show that the proposed method outperforms state-of-the-art multimodal methods and is robust to the perturbations of the topometric map.
1 code implementation • 6 Apr 2021 • Chen Min, Jiaolong Xu, Liang Xiao, Dawei Zhao, Yiming Nie, Bin Dai
Deep learning has recently demonstrated its promising performance for vision-based parking-slot detection.
no code implementations • 28 Nov 2020 • Helin Yang, Jun Zhao, Zehui Xiong, Kwok-Yan Lam, Sumei Sun, Liang Xiao
However, due to the privacy concerns of devices and limited computation or communication resource of UAVs, it is impractical to send raw data of devices to UAV servers for model training.
no code implementations • 13 Aug 2020 • Jie Song, Liang Xiao, Mohsen Molaei, Zhichao Lian
In this way, rich image appearance models together with more contextual information are integrated by learning a series of decision tree ensembles.
1 code implementation • 2 Aug 2020 • Yu Shen, Sijie Zhu, Chen Chen, Qian Du, Liang Xiao, Jianyu Chen, Delu Pan
Therefore, to incorporate the long-range contextual information, a deep fully convolutional network (FCN) with an efficient non-local module, named ENL-FCN, is proposed for HSI classification.
no code implementations • 6 May 2020 • Li Wang, Dawei Zhao, Tao Wu, Hao Fu, Zhiyu Wang, Liang Xiao, Xin Xu, Bin Dai
3D moving object detection is one of the most critical tasks in dynamic scene analysis.
no code implementations • 27 Feb 2020 • Helin Yang, Zehui Xiong, Jun Zhao, Dusit Niyato, Liang Xiao, Qingqing Wu
As the system is highly dynamic and complex, and it is challenging to address the non-convex optimization problem, a novel deep reinforcement learning (DRL)-based secure beamforming approach is firstly proposed to achieve the optimal beamforming policy against eavesdroppers in dynamic environments.
no code implementations • 13 Feb 2020 • Pei-Gen Ye, Yuan-Gen Wang, Jin Li, Liang Xiao
This letter presents a fast reinforcement learning algorithm for anti-jamming communications which chooses previous action with probability $\tau$ and applies $\epsilon$-greedy with probability $(1-\tau)$.
1 code implementation • 25 Jul 2019 • Jiaolong Xu, Liang Xiao, Antonio M. Lopez
Additionally, we propose two complementary strategies to further boost the domain adaptation accuracy on semantic segmentation within our method, consisting of prediction layer alignment and batch normalization calibration.
no code implementations • 23 Jan 2018 • Liang Xiao, Donghua Jiang, Dongjin Xu, Ning An
In order to stimulate secure sensing for Internet of Things (IoT) applications such as healthcare and traffic monitoring, mobile crowdsensing (MCS) systems have to address security threats, such as jamming, spoofing and faked sensing attacks, during both the sensing and the information exchange processes in large-scale dynamic and heterogenous networks.
no code implementations • 19 Jan 2018 • Liang Xiao, Xingyu Xiao, Canhuang Dai, Mugen Pengy, Li-Chun Wang, H. Vincent Poor
The Nash quilibrium (NE) of the game is provided, revealing the conditions under which the local energy generation satisfies the energy demand of the MG and providing the performance bound of the energy trading scheme.
Systems and Control
no code implementations • 19 Dec 2017 • Liang Xiao, Guoan Han, Donghua Jiang, Hongzi Zhu, Yanyong Zhang, H. Vincent Poor
It is shown that, by applying reinforcement learning techniques, a mobile device can achieve an optimal communication policy without the need to know the jamming and interference model and the radio channel model in a dynamic game framework.
no code implementations • NeurIPS 2017 • Zhen He, Shao-Bing Gao, Liang Xiao, Daxue Liu, Hangen He, David Barber
The capacity of an LSTM network can be increased by widening and adding layers.