13 results on '"Liu, Limin"'
Search Results
2. Mask Reference Image Quality Assessment
- Author
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Xiao, Pengxiang, He, Shuai, Liu, Limin, and Ming, Anlong
- Subjects
Computer Science - Computer Vision and Pattern Recognition ,Electrical Engineering and Systems Science - Image and Video Processing - Abstract
Understanding semantic information is an essential step in knowing what is being learned in both full-reference (FR) and no-reference (NR) image quality assessment (IQA) methods. However, especially for many severely distorted images, even if there is an undistorted image as a reference (FR-IQA), it is difficult to perceive the lost semantic and texture information of distorted images directly. In this paper, we propose a Mask Reference IQA (MR-IQA) method that masks specific patches of a distorted image and supplements missing patches with the reference image patches. In this way, our model only needs to input the reconstructed image for quality assessment. First, we design a mask generator to select the best candidate patches from reference images and supplement the lost semantic information in distorted images, thus providing more reference for quality assessment; in addition, the different masked patches imply different data augmentations, which favors model training and reduces overfitting. Second, we provide a Mask Reference Network (MRNet): the dedicated modules can prevent disturbances due to masked patches and help eliminate the patch discontinuity in the reconstructed image. Our method achieves state-of-the-art performances on the benchmark KADID-10k, LIVE and CSIQ datasets and has better generalization performance across datasets. The code and results are available in the supplementary material., Comment: 10 pages, 6 figures
- Published
- 2023
3. Clustering-Induced Generative Incomplete Image-Text Clustering (CIGIT-C)
- Author
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Guo, Dongjin, Su, Xiaoming, Wang, Jiatai, Liu, Limin, Pei, Zhiyong, and Xu, Zhiwei
- Subjects
Computer Science - Artificial Intelligence - Abstract
The target of image-text clustering (ITC) is to find correct clusters by integrating complementary and consistent information of multi-modalities for these heterogeneous samples. However, the majority of current studies analyse ITC on the ideal premise that the samples in every modality are complete. This presumption, however, is not always valid in real-world situations. The missing data issue degenerates the image-text feature learning performance and will finally affect the generalization abilities in ITC tasks. Although a series of methods have been proposed to address this incomplete image text clustering issue (IITC), the following problems still exist: 1) most existing methods hardly consider the distinct gap between heterogeneous feature domains. 2) For missing data, the representations generated by existing methods are rarely guaranteed to suit clustering tasks. 3) Existing methods do not tap into the latent connections both inter and intra modalities. In this paper, we propose a Clustering-Induced Generative Incomplete Image-Text Clustering(CIGIT-C) network to address the challenges above. More specifically, we first use modality-specific encoders to map original features to more distinctive subspaces. The latent connections between intra and inter-modalities are thoroughly explored by using the adversarial generating network to produce one modality conditional on the other modality. Finally, we update the corresponding modalityspecific encoders using two KL divergence losses. Experiment results on public image-text datasets demonstrated that the suggested method outperforms and is more effective in the IITC job., Comment: 13 pages,12 figures
- Published
- 2022
4. Self-supervised Image Clustering from Multiple Incomplete Views via Constrastive Complementary Generation
- Author
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Wang, Jiatai, Xu, Zhiwei, Yang, Xuewen, Guo, Dongjin, and Liu, Limin
- Subjects
Computer Science - Computer Vision and Pattern Recognition - Abstract
Incomplete Multi-View Clustering aims to enhance clustering performance by using data from multiple modalities. Despite the fact that several approaches for studying this issue have been proposed, the following drawbacks still persist: 1) It's difficult to learn latent representations that account for complementarity yet consistency without using label information; 2) and thus fails to take full advantage of the hidden information in incomplete data results in suboptimal clustering performance when complete data is scarce. In this paper, we propose Contrastive Incomplete Multi-View Image Clustering with Generative Adversarial Networks (CIMIC-GAN), which uses GAN to fill in incomplete data and uses double contrastive learning to learn consistency on complete and incomplete data. More specifically, considering diversity and complementary information among multiple modalities, we incorporate autoencoding representation of complete and incomplete data into double contrastive learning to achieve learning consistency. Integrating GANs into the autoencoding process can not only take full advantage of new features of incomplete data, but also better generalize the model in the presence of high data missing rates. Experiments conducted on \textcolor{black}{four} extensively-used datasets show that CIMIC-GAN outperforms state-of-the-art incomplete multi-View clustering methods.
- Published
- 2022
- Full Text
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5. Estimation & Recognition under Perspective of Random-Fuzzy Dual Interpretation of Unknown Quantity: with Demonstration of IMM Filter
- Author
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Mei, Wei, Xu, Yunfeng, and Liu, Limin
- Subjects
Electrical Engineering and Systems Science - Systems and Control ,Computer Science - Artificial Intelligence ,Electrical Engineering and Systems Science - Signal Processing ,Mathematics - Probability ,Statistics - Applications - Abstract
This paper is to consider the problems of estimation and recognition from the perspective of sigma-max inference (probability-possibility inference), with a focus on discovering whether some of the unknown quantities involved could be more faithfully modeled as fuzzy uncertainty. Two related key issues are addressed: 1) the random-fuzzy dual interpretation of unknown quantity being estimated; 2) the principle of selecting sigma-max operator for practical problems, such as estimation and recognition. Our perspective, conceived from definitions of randomness and fuzziness, is that continuous unknown quantity involved in estimation with inaccurate prior should be more appropriately modeled as randomness and handled by sigma inference; whereas discrete unknown quantity involved in recognition with insufficient (and inaccurate) prior could be better modeled as fuzziness and handled by max inference. The philosophy was demonstrated by an updated version of the well-known interacting multiple model (IMM) filter, for which the jump Markovian System is reformulated as a hybrid uncertainty system, with continuous state evolution modeled as usual as model-conditioned stochastic system and discrete mode transitions modeled as fuzzy system by a possibility (instead of probability) transition matrix, and hypotheses mixing is conducted by using the operation of "max" instead of "sigma". For our example of maneuvering target tracking using simulated data from both a short-range fire control radar and a long-range surveillance radar, the updated IMM filter shows significant improvement over the classic IMM filter, due to its peculiarity of hard decision of system model and a faster response to the transition of discrete mode., Comment: 15 pages, 11 figures, code available
- Published
- 2021
6. The Sigma-Max System Induced from Randomness and Fuzziness
- Author
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Mei, Wei, Li, Ming, Cheng, Yuanzeng, and Liu, Limin
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Computer Science - Artificial Intelligence ,Computer Science - Logic in Computer Science ,Mathematics - Probability ,03B48, 03B52, 60A05, 68T07 - Abstract
This paper managed to induce probability theory (sigma system) and possibility theory (max system) respectively from randomness and fuzziness, through which the premature theory of possibility is expected to be well founded. Such an objective is achieved by addressing three open key issues: a) the lack of clear mathematical definitions of randomness and fuzziness; b) the lack of intuitive mathematical definition of possibility; c) the lack of abstraction procedure of the axiomatic definitions of probability/possibility from their intuitive definitions. Especially, the last issue involves the question why the key axiom of "maxitivity" is adopted for possibility measure. By taking advantage of properties of the well-defined randomness and fuzziness, we derived the important conclusion that "max" is the only but un-strict disjunctive operator that is applicable across the fuzzy event space, and is an exact operator for fuzzy feature extraction that assures the max inference is an exact mechanism. It is fair to claim that the long-standing problem of lack of consensus to the foundation of possibility theory is well resolved, which would facilitate wider adoption of possibility theory in practice and promote cross prosperity of the two uncertainty theories of probability and possibility.
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- 2021
7. Moire Superlattice Modulations in Single-Unit-Cell FeTe Films Grown on NbSe2 Single Crystals
- Author
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Deng, Han-Bin, Li, Yuan, Feng, Zili, Guan, Jian-Yu, Yu1, Xin, Huang, Xiong, Liu, Rui-Zhe, Zhu, Chang-Jiang, Liu, Limin, Sun, Ying-Kai, Peng, Xi-liang, Li, Shuai-Shuai, Du, Xin, Wang, Zheng, Wu, Rui, Yin, Jia-Xin, Shi, You-Guo, and Mao, Han-Qing
- Subjects
Condensed Matter - Strongly Correlated Electrons ,Condensed Matter - Mesoscale and Nanoscale Physics ,Condensed Matter - Superconductivity - Abstract
Interface can be a fertile ground for exotic quantum states, including topological superconductivity, Majorana mode, fractal quantum Hall effect, unconventional superconductivity, Mott insulator, etc. Here we grow single-unit-cell (1UC) FeTe film on NbSe2 single crystal by molecular beam epitaxy (MBE) and investigate the film in-situ with home-made cryogenic scanning tunneling microscopy (STM) and non-contact atomic force microscopy (AFM) combined system. We find different stripe-like superlattice modulations on grown FeTe film with different misorientation angles with respect to NbSe2 substrate. We show that these stripe-like superlattice modulations can be understood as moire pattern forming between FeTe film and NbSe2 substrate. Our results indicate that the interface between FeTe and NbSe2 is atomically sharp. By STM-AFM combined measurement, we suggest the moire superlattice modulations have an electronic origin when the misorientation angle is relatively small (<= 3 degree) and have structural relaxation when the misorientation angle is relatively large (>= 10 degree)., Comment: 10 pages, 4 figures
- Published
- 2021
- Full Text
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8. Direct Observation of the Scale Relation between Density of States and Pairing Gap in a Dirty Superconductor
- Author
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Zhu, Chang-Jiang, Liu, Limin, Song, Peng-Bo, Deng, Han-Bin, Yi, Chang-Jiang, Sun, Ying-Kai, Wu, R., Yin, Jia-Xin, Shi, Youguo, Wang, Ziqiang, and Pan, Shuheng H.
- Subjects
Condensed Matter - Superconductivity - Abstract
Theories and experiments on dirty superconductors are sophisticated but important for both fundamentals and applications. It becomes more challenging when magnetic fields are present, because the field distribution, the electron density of states, and the superconducting pairing potentials are nonuniform. Here we present tunneling microspectroscopic experiments on NbC single crystals and show that NbC is a homogeneous dirty superconductor. When applying magnetic fields to the sample, we observe that the zero-energy local density of states and the pairing energy gap follow an explicit scale relation proposed by de Gennes for homogeneous dirty superconductors in high magnetic fields. Surprisingly, our experimental findings suggest that the validity of the scale relation extends to magnetic field strengths far below the upper critical field and call for new nonperturbative understanding of this fundamental property in dirty superconductors. On the practical side, we use the observed scale relation to drive a simple and straightforward experimental scheme for extracting the superconducting coherence length of a dirty superconductor in magnetic fields.
- Published
- 2021
- Full Text
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9. Thermal dynamics of charge density wave pinning in ZrTe3
- Author
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Liu, Limin, Zhu, Changjiang, Liu, Z. Y., Deng, Hanbin, Zhou, X. B., Li, Yuan, Sun, Yingkai, Huang, Xiong, Li, Shuaishuai, Du, Xin, Wang, Zheng, Guan, Tong, Mao, Hanqing, Sui, Y., Wu, Rui, Yin, Jia-Xin, Cheng, J. -G., and Pan, Shuheng H.
- Subjects
Condensed Matter - Strongly Correlated Electrons ,Condensed Matter - Materials Science - Abstract
Impurity pinning has long been discussed to have a profound effect on the dynamics of an incommensurate charge density wave (CDW), which would otherwise slide through the lattice without resistance. Here we visualize the impurity pinning evolution of the CDW in ZrTe3 using the variable temperature scanning tunneling microscopy (STM). At low temperatures, we observe a quasi-1D incommensurate CDW modulation moderately correlated to the impurity positions, indicating a weak impurity pinning. As we raise the sample temperature, the CDW modulation gets progressively weakened and distorted, while the correlation with the impurities becomes stronger. Above the CDW transition temperature, short-range modulations persist with the phase almost all pinned by impurities. The evolution from weak to strong impurity pinning through the CDW transition can be understood as a result of losing phase rigidity.
- Published
- 2021
- Full Text
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10. Role of anion in the pairing interaction of iron-based superconductivity
- Author
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Yin, J. -X., Zhao, Y. Y., Wu, Zheng, Wu, X. X., Kreisel, A., Andersen, B. M., Macam, Gennevieve, Zhou, Sen, Wu, Rui, Liu, Limin, Deng, Hanbin, Zhu, Changjiang, Li, Yuan, Sun, Yingkai, Huang, Zhi-Quan, Chuang, Feng-Chuan, Lin, Hsin, Ting, C. -S., Hu, J. -P., Wang, Z. Q., Dai, P. C., Ding, H., and Pan, S. H.
- Subjects
Condensed Matter - Superconductivity ,Condensed Matter - Materials Science - Abstract
High-temperature iron-based superconductivity develops in a structure with unusual lattice-orbital geometry, based on a planar layer of Fe atoms with 3d orbitals and tetrahedrally coordinated by anions. Here we elucidate the electronic role of anions in the iron-based superconductors utilizing state-of-the-art scanning tunneling microscopy. By measuring the local electronic structure, we find that As anion in Ba0.4K0.6Fe2As2 has a striking impact on the electron pairing. The superconducting electronic feature can be switched off/on by removing/restoring As atoms on Fe layer at the atomic scale. Our analysis shows that this remarkable atomic switch effect is related to the geometrical cooperation between anion mediated hopping and unconventional pairing interaction. Our results uncover that the local Fe-anion coupling is fundamental for the pairing interaction of iron-based superconductivity, and promise the potential of bottom-up engineering of electron pairing.
- Published
- 2020
11. Towards Accurate Deceptive Opinion Spam Detection based on Word Order-preserving CNN
- Author
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Zhao, Siyuan, Xu, Zhiwei, Liu, Limin, and Guo, Mengjie
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Computer Science - Computation and Language - Abstract
Nowadays, deep learning has been widely used. In natural language learning, the analysis of complex semantics has been achieved because of its high degree of flexibility. The deceptive opinions detection is an important application area in deep learning model, and related mechanisms have been given attention and researched. On-line opinions are quite short, varied types and content. In order to effectively identify deceptive opinions, we need to comprehensively study the characteristics of deceptive opinions, and explore novel characteristics besides the textual semantics and emotional polarity that have been widely used in text analysis. The detection mechanism based on deep learning has better self-adaptability and can effectively identify all kinds of deceptive opinions. In this paper, we optimize the convolution neural network model by embedding the word order characteristics in its convolution layer and pooling layer, which makes convolution neural network more suitable for various text classification and deceptive opinions detection. The TensorFlow-based experiments demonstrate that the detection mechanism proposed in this paper achieve more accurate deceptive opinion detection results.
- Published
- 2017
12. Context-aware System Service Call-oriented Symbolic Execution of Android Framework with Application to Exploit Generation
- Author
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Luo, Lannan, Zeng, Qiang, Cao, Chen, Chen, Kai, Liu, Jian, Liu, Limin, Gao, Neng, Yang, Min, Xing, Xinyu, and Liu, Peng
- Subjects
Computer Science - Cryptography and Security ,Computer Science - Software Engineering - Abstract
Android Framework is a layer of software that exists in every Android system managing resources of all Android apps. A vulnerability in Android Framework can lead to severe hacks, such as destroying user data and leaking private information. With tens of millions of Android devices unpatched due to Android fragmentation, vulnerabilities in Android Framework certainly attract attackers to exploit them. So far, enormous manual effort is needed to craft such exploits. To our knowledge, no research has been done on automatic generation of exploits that take advantage of Android Framework vulnerabilities. We make a first step towards this goal by applying symbolic execution of Android Framework to finding bugs and generating exploits. Several challenges have been raised by the task. (1) The information of an app flows to Android Framework in multiple intricate steps, making it difficult to identify symbolic inputs. (2) Android Framework has a complex initialization phase, which exacerbates the state space explosion problem. (3) A straightforward design that builds the symbolic executor as a layer inside the Android system will not work well: not only does the implementation have to ensure the compatibility with the Android system, but it needs to be maintained whenever Android gets updated. We present novel ideas and techniques to resolve the challenges, and have built the first system for symbolic execution of Android Framework. It fundamentally changes the state of the art in exploit generation on the Android system, and has been applied to constructing new techniques for finding vulnerabilities.
- Published
- 2016
13. TSM: Efficient Thermal and Server Management for Greening Data Centers.
- Author
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Wan, Jianxiong, Zhang, Gefei, Liu, Limin, and Zhang, Ran
- Published
- 2015
- Full Text
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