ORCID Profile
0000-0002-4427-2687
Current Organisations
University of Wollongong
,
University of Western Australia
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Publisher: MDPI AG
Date: 27-07-2015
DOI: 10.3390/NU7085274
Publisher: IEEE
Date: 10-2008
Publisher: Springer Berlin Heidelberg
Date: 2008
Publisher: IEEE
Date: 12-2008
DOI: 10.1109/MMIT.2008.66
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2022
Publisher: IEEE
Date: 2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2008
Publisher: IEEE
Date: 07-2013
Publisher: IEEE
Date: 06-2010
Publisher: Springer Science and Business Media LLC
Date: 09-12-2017
DOI: 10.1007/S11517-017-1763-2
Abstract: Reconstructing magnetic resonance images from unders led k-space data is a challenging problem. This paper introduces a novel method of image reconstruction from unders led k-space data based on the concept of singularizing operators and a novel singular k-space model. Exploring the sparsity of an image in the k-space, the singular k-space model (SKM) is proposed in terms of the k-space functions of a singularizing operator. The singularizing operator is constructed by combining basic difference operators. An algorithm is developed to reliably estimate the model parameters from unders led k-space data. The estimated parameters are then used to recover the missing k-space data through the model, subsequently achieving high-quality reconstruction of the image using inverse Fourier transform. Experiments on physical phantom and real brain MR images have shown that the proposed SKM method constantly outperforms the popular total variation (TV) and the classical zero-filling (ZF) methods regardless of the unders ling rates, the noise levels, and the image structures. For the same objective quality of the reconstructed images, the proposed method requires much less k-space data than the TV method. The SKM method is an effective method for fast MRI reconstruction from the unders led k-space data. Graphical abstract Two Real Images and their sparsified images by singularizing operator.
Publisher: IEEE
Date: 12-2010
DOI: 10.1109/ISM.2010.37
Publisher: IEEE
Date: 11-2009
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Publisher: Elsevier BV
Date: 10-2018
Publisher: Informa UK Limited
Date: 14-11-2023
Publisher: IEEE
Date: 09-2010
Publisher: Springer Berlin Heidelberg
Date: 2009
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2016
Publisher: IEEE
Date: 07-2016
Publisher: Hindawi Limited
Date: 2008
DOI: 10.1155/2008/542918
Abstract: Multiplayer online games (MOGs) have become increasingly popular because of the opportunity they provide for collaboration, communication, and interaction. However, compared with ordinary human communication, MOG still has several limitations, especially in communication using facial expressions. Although detailed facial animation has already been achieved in a number of MOGs, players have to use text commands to control the expressions of avatars. In this paper, we propose an automatic expression recognition system that can be integrated into an MOG to control the facial expressions of avatars. To meet the specific requirements of such a system, a number of algorithms are studied, improved, and extended. In particular, Viola and Jones face-detection method is extended to detect small-scale key facial components and fixed facial landmarks are used to reduce the computational load with little performance degradation in the recognition accuracy.
Publisher: IGI Global
Date: 2009
DOI: 10.4018/978-1-60566-900-7.CH010
Abstract: This chapter first presents a brief review of the recent development in human action recognition. In particular, the principle and shortcomings of the conventional Hidden Markov Model (HMM) and its variants are discussed. We then introduce an expandable graphical model that represents the dynamics of human actions using a weighted directed graph, referred to as action graph. Unlike the conventional HMM, the action graph is shared by all actions to be recognized with each action being encoded in one or multiple paths and, thus, can be effectively and efficiently trained from a small number of s les. Furthermore, the action graph is expandable to incorporate new actions without being retrained and compromised. To verify the performance of the proposed expandable graphic model, a system that learns and recognizes human actions from sequences of silhouettes is developed and promising results are obtained.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2022
Publisher: Institution of Engineering and Technology (IET)
Date: 2012
DOI: 10.1049/EL.2012.0015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2017
Publisher: IEEE
Date: 07-2013
Publisher: Springer Berlin Heidelberg
Date: 2012
Publisher: IEEE
Date: 05-2002
Publisher: Springer Science and Business Media LLC
Date: 30-07-2020
Publisher: IEEE
Date: 11-2013
Publisher: Elsevier BV
Date: 12-2016
Publisher: Wiley
Date: 16-12-2012
DOI: 10.1002/JMRI.23538
Abstract: To shorten acquisition time by means of both partial scanning and partial echo acquisition and to reconstruct images from such 2D partial k-space acquisitions. We propose an approach to reconstructing magnetic resonance images from 2D truncated k-space in which the k-space is truncated in both phase- and frequency-encoding directions. Unlike conventional reconstruction techniques, the proposed approach is based on a newly developed 2D singularity function analysis (SFA) model and a sparse representation of an image whose parameters can be estimated from the 2D partial k-space data. Such a sparse representation leads to an accurate recovery of the missing k-space data and, hence, an accurate reconstruction of the image. The proposed approach can reconstruct an image from as little as 20%-30% of the k-space data and the quality of the reconstructed image is comparable to the reference image that is reconstructed from the complete k-space data. Despite the high asymmetry of a 2D truncated k-space, the proposed approach allows for accurate reconstruction without the need of phase correction and, thus, overcomes the assumption of slow phase variations that is usually required by the existing reconstruction methods. It provides a new way of fast imaging for applications that require a significant reduction of the acquisition time.
Publisher: Elsevier BV
Date: 11-2012
DOI: 10.1016/J.JMR.2012.08.014
Abstract: Truncation artefacts are often present in many archived clinical magnetic resonance (MR) images due to the need of shortening the acquisition time by s ling a part of their k-space. This artificial information degrades the quality of the image and may h er clinical diagnosis. In this paper, we propose a novel method to remove the artefacts by recovering the missing k-space or spectral data. The method consists of four steps: (a) estimating the truncated k-space from the images containing truncations artefacts, (b) computing the parameters of the sparse representation of the difference image of an image from the estimated truncated k-space, (c) recovering the missing spectral data using the parameters computed in (b), and (d) obtaining the artefact-removed image through inverse Fourier transform of the estimated and the recovered spectral data. Experiments on both simulated and real MR images have shown that the proposed method effectively removes truncation artefacts while preserving image quality and outperforms both the conventional Hamming window method and the popular TV method.
Publisher: Springer Berlin Heidelberg
Date: 2007
Publisher: IEEE
Date: 11-2006
DOI: 10.1109/AVSS.2006.10
Publisher: SPIE
Date: 19-09-1997
DOI: 10.1117/12.279625
Publisher: IEEE
Date: 11-2013
Publisher: IEEE
Date: 11-2009
Publisher: Springer International Publishing
Date: 2015
Publisher: IEEE
Date: 10-2011
Publisher: IEEE
Date: 07-2006
Publisher: IEEE
Date: 2009
Publisher: IEEE
Date: 11-2011
Publisher: American Chemical Society (ACS)
Date: 18-05-2009
DOI: 10.1021/BI9000672
Publisher: Elsevier BV
Date: 05-2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2023
Publisher: Elsevier BV
Date: 10-2024
Publisher: Springer Science and Business Media LLC
Date: 05-03-2016
Publisher: IEEE
Date: 2009
Publisher: IEEE
Date: 11-2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2019
Publisher: IEEE
Date: 06-2015
Publisher: Elsevier BV
Date: 12-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2016
Publisher: IEEE
Date: 12-2009
Publisher: Elsevier BV
Date: 05-2008
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2016
DOI: 10.1109/MMUL.2016.19
Publisher: IEEE
Date: 09-2013
Publisher: Elsevier BV
Date: 04-2017
Publisher: Springer Berlin Heidelberg
Date: 2009
Publisher: Springer Berlin Heidelberg
Date: 2006
DOI: 10.1007/11811305_61
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2005
Publisher: Elsevier BV
Date: 09-2014
Publisher: IEEE
Date: 07-2017
Publisher: IEEE
Date: 07-2017
Publisher: Springer Berlin Heidelberg
Date: 2007
Publisher: IEEE
Date: 07-2007
Publisher: Institution of Engineering and Technology (IET)
Date: 2011
DOI: 10.1049/EL.2010.3256
Publisher: IEEE
Date: 10-2011
Publisher: Elsevier BV
Date: 12-2017
Publisher: IEEE
Date: 12-2017
Publisher: Springer Science and Business Media LLC
Date: 07-11-2019
Publisher: IEEE
Date: 11-2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: IEEE
Date: 12-2016
Publisher: Springer Berlin Heidelberg
Date: 2006
DOI: 10.1007/11738695_25
Publisher: Springer Science and Business Media LLC
Date: 30-05-2016
Publisher: IEEE
Date: 11-2010
Publisher: IEEE
Date: 2005
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2022
Publisher: Elsevier BV
Date: 10-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: IEEE
Date: 10-2017
Publisher: Springer International Publishing
Date: 2014
Publisher: IEEE
Date: 11-2009
Publisher: Springer International Publishing
Date: 2018
Publisher: IEEE
Date: 10-2017
Publisher: Elsevier BV
Date: 04-2019
Publisher: IEEE
Date: 06-2009
Publisher: IEEE
Date: 11-2015
Publisher: IEEE
Date: 2002
Publisher: Springer Science and Business Media LLC
Date: 02-08-2012
Publisher: IEEE
Date: 11-2009
Publisher: IEEE
Date: 09-2011
Publisher: IEEE
Date: 10-2008
Publisher: IEEE
Date: 10-2011
Publisher: IEEE
Date: 2005
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2018
Publisher: Elsevier BV
Date: 12-2019
Publisher: IEEE
Date: 05-2002
Publisher: Elsevier BV
Date: 06-2013
Publisher: Trans Tech Publications, Ltd.
Date: 2012
DOI: 10.4028/WWW.SCIENTIFIC.NET/AMR.459.364
Abstract: The paper proposes an approach for setting the size of project buffer based on the theory of unascertained rational numbers and critical chain management. This method applies the optimistic time into programming schedule plan and using the addition operation of unascertained rational numbers to obtain the unascertained schedule plan, to finish and generate cumulative reliability. This technique is applied to calculate the buffer time by using the optimistic construction period and total project period when finishing reliability is 90%. This feasibility of the model has been proved by an ex le
Publisher: IEEE
Date: 08-2010
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-0001
Publisher: IEEE
Date: 10-2017
Publisher: Association for Computing Machinery (ACM)
Date: 05-2013
Abstract: Getting familiar with a face is an important cognitive process in human perception of faces, but little study has been reported on how to objectively measure the degree of familiarity. In this article, a method is proposed to quantitatively measure the familiarity of a face with respect to a set of reference faces that have been seen previously. The proposed method models the context-free and context-dependent forms of familiarity suggested by psychological studies and accounts for the key factors, namely exposure frequency, exposure intensity and similar exposure, that affect human perception of face familiarity. Specifically, the method ides the reference set into nonexclusive groups and measures the familiarity of a given face by aggregating the similarities of the face to the in idual groups. In addition, the nonnegative matrix factorization (NMF) is extended in this paper to learn a compact and localized subspace representation for measuring the similarities of the face with respect to the in idual groups. The proposed method has been evaluated through experiments that follow the protocols commonly used in psychological studies and has been compared with subjective evaluation. Results have shown that the proposed measurement is highly consistent with the subjective judgment of face familiarity. Moreover, a face recognition method is devised using the concept of face familiarity and the results on the standard FERET evaluation protocols have further verified the efficacy of the proposed familiarity measurement.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2010
Publisher: IEEE
Date: 10-2008
Publisher: Association for Computing Machinery (ACM)
Date: 12-07-2023
DOI: 10.1145/3596445
Abstract: This article proposes a network, referred to as Multi-View Stereo TRansformer (MVSTR) for depth estimation from multi-view images. By modeling long-range dependencies and epipolar geometry, the proposed MVSTR is capable of extracting dense features with global context and 3D consistency, which are crucial for reliable matching in multi-view stereo (MVS). Specifically, to tackle the problem of the limited receptive field of existing CNN-based MVS methods, a global-context Transformer module is designed to establish intra-view long-range dependencies so that global contextual features of each view are obtained. In addition, to further enable features of each view to be 3D consistent, a 3D-consistency Transformer module with an epipolar feature s ler is built, where epipolar geometry is modeled to effectively facilitate cross-view interaction. Experimental results show that the proposed MVSTR achieves the best overall performance on the DTU dataset and demonstrates strong generalization on the Tanks & Temples benchmark dataset.
Publisher: ACM
Date: 10-2016
Publisher: Wiley
Date: 19-06-2008
Publisher: Elsevier BV
Date: 07-2017
DOI: 10.1016/J.MRI.2017.03.008
Abstract: Single image super-resolution (SR) is highly desired in many fields but obtaining it is often technically limited in practice. The purpose of this study was to propose a simple, rapid and robust single image SR method in magnetic resonance (MR) imaging (MRI). The idea is based on the mathematical formulation of the intrinsic link in k-space between a given (modulus) low-resolution (LR) image and the desired SR image. The method consists of two steps: 1) estimating the low-frequency k-space data of the desired SR image from a single LR image 2) reconstructing the SR image using the estimated low-frequency and zero-filled high-frequency k-space data. The method was evaluated on digital phantom images, physical phantom MR images and real brain MR images, and compared with existing SR methods. The proposed SR method exhibited a good robustness by reaching a clearly higher PSNR (25.77dB) and SSIM (0.991) averaged over different noise levels in comparison with existing edge-guided nonlinear interpolation (EGNI) (PSNR=23.78dB, SSIM=0.983), zero-filling (ZF) (PSNR=24.09dB, SSIM=0.985) and total variation (TV) (PSNR=24.54dB, SSIM=0.987) methods while presenting the same order of computation time as the ZF method but being much faster than the EGNI or TV method. The average PSNR or SSIM over different slice images of the proposed method (PSNR=26.33 dB or SSIM=0.955) was also higher than the EGNI (PSNR=25.07dB or SSIM=0.952), ZF (PSNR=24.97dB or SSIM=0.950) and TV (PSNR=25.70dB or SSIM=0.953) methods, demonstrating its good robustness to variation in anatomical structure of the images. Meanwhile, the proposed method always produced less ringing artifacts than the ZF method, gave a clearer image than the EGNI method, and did not exhibit any blocking effect presented in the TV method. In addition, the proposed method yielded the highest spatial consistency in the inter-slice dimension among the four methods. This study proposed a fast, robust and efficient single image SR method with high spatial consistency in the inter-slice dimension for clinical MR images by estimating the low-frequency k-space data of the desired SR image from a single spatial modulus LR image.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2023
Publisher: Institution of Engineering and Technology (IET)
Date: 2011
Publisher: IEEE
Date: 06-2008
Publisher: ACM
Date: 13-10-2015
Publisher: Springer Berlin Heidelberg
Date: 2006
DOI: 10.1007/11922162_17
Publisher: MDPI AG
Date: 10-06-2020
DOI: 10.3390/S20113305
Abstract: The paper presents a novel hybrid network for large-scale action recognition from multiple modalities. The network is built upon the proposed weighted dynamic images. It effectively leverages the strengths of the emerging Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) based approaches to specifically address the challenges that occur in large-scale action recognition and are not fully dealt with by the state-of-the-art methods. Specifically, the proposed hybrid network consists of a CNN based component and an RNN based component. Features extracted by the two components are fused through canonical correlation analysis and then fed to a linear Support Vector Machine (SVM) for classification. The proposed network achieved state-of-the-art results on the ChaLearn LAP IsoGD, NTU RGB+D and Multi-modal & Multi-view & Interactive ( M 2 I ) datasets and outperformed existing methods by a large margin (over 10 percentage points in some cases).
Publisher: IEEE
Date: 12-2015
Publisher: Springer Berlin Heidelberg
Date: 2008
Publisher: IEEE
Date: 2012
Publisher: Springer Berlin Heidelberg
Date: 2009
Publisher: Proceedings of the National Academy of Sciences
Date: 16-12-2008
Abstract: Tyrosine trans -phosphorylation is a key event in receptor tyrosine kinase signaling, yet, the structural basis for this process has eluded definition. Here, we present the crystal structure of the FGF receptor 2 kinases caught in the act of trans -phosphorylation of Y769, the major C-terminal phosphorylation site. The structure reveals that enzyme- and substrate-acting kinases engage each other through elaborate and specific interactions not only in the immediate vicinity of Y769 and the enzyme active site, but also in regions that are as much of 18 Å away from D626, the catalytic base in the enzyme active site. These interactions lead to an unprecedented level of specificity and precision during the trans -phosphorylation on Y769. Time-resolved mass spectrometry analysis supports the observed mechanism of trans -phosphorylation. Our data provide a molecular framework for understanding the mechanism of action of Kallmann syndrome mutations and the order of trans -phosphorylation reactions in FGFRs. We propose that the salient mechanistic features of Y769 trans -phosphorylation are applicable to trans -phosphorylation of the equivalent major phosphorylation sites in many other RTKs.
Publisher: IEEE
Date: 12-2019
Publisher: IEEE
Date: 07-2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2016
Publisher: Springer Berlin Heidelberg
Date: 2009
Publisher: Association for Computing Machinery (ACM)
Date: 17-02-2019
DOI: 10.1145/3291124
Abstract: This article takes a problem-oriented perspective and presents a comprehensive review of transfer-learning methods, both shallow and deep, for cross-dataset visual recognition. Specifically, it categorises the cross-dataset recognition into 17 problems based on a set of carefully chosen data and label attributes. Such a problem-oriented taxonomy has allowed us to examine how different transfer-learning approaches tackle each problem and how well each problem has been researched to date. The comprehensive problem-oriented review of the advances in transfer learning with respect to the problem has not only revealed the challenges in transfer learning for visual recognition but also the problems (e.g., 8 of the 17 problems) that have been scarcely studied. This survey not only presents an up-to-date technical review for researchers but also a systematic approach and a reference for a machine-learning practitioner to categorise a real problem and to look up for a possible solution accordingly.
Publisher: Association for Computing Machinery (ACM)
Date: 31-05-2023
DOI: 10.1145/3587467
Abstract: Novel view synthesis aims to generate novel views from one or more given source views. Although existing methods have achieved promising performance, they usually require paired views with different poses to learn a pixel transformation. This article proposes an unsupervised network to learn such a pixel transformation from a single source image. In particular, the network consists of a token transformation module that facilities the transformation of the features extracted from a source image into an intrinsic representation with respect to a pre-defined reference pose and a view generation module that synthesizes an arbitrary view from the representation. The learned transformation allows us to synthesize a novel view from any single source image of an unknown pose. Experiments on the widely used view synthesis datasets have demonstrated that the proposed network is able to produce comparable results to the state-of-the-art methods despite the fact that learning is unsupervised and only a single source image is required for generating a novel view. The code will be available upon the acceptance of the article.
Publisher: IEEE
Date: 10-2014
Publisher: Springer Berlin Heidelberg
Date: 2010
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: IEEE
Date: 09-2013
Publisher: IEEE
Date: 07-2011
Publisher: Elsevier BV
Date: 03-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2016
Publisher: IEEE
Date: 2009
Publisher: Elsevier BV
Date: 07-2008
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2018
Publisher: IEEE
Date: 06-2018
Publisher: IEEE
Date: 03-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2015
Publisher: ACM
Date: 08-10-2018
Publisher: Springer Berlin Heidelberg
Date: 2009
Publisher: Springer Nature Switzerland
Date: 2022
Publisher: IEEE
Date: 06-2018
Publisher: IEEE
Date: 07-2017
DOI: 10.1109/CVPR.2017.52
Publisher: Trans Tech Publications, Ltd.
Date: 2012
DOI: 10.4028/WWW.SCIENTIFIC.NET/AMR.459.145
Abstract: The optimization of the three objectives, time, cost and quality, is the important project management content. This paper applies co-evolutionary algorithm to the optimization of the three engineering project objectives. The populations of time, cost and quality are separately designed for cooperative evolutionary operators in the paper, which are coordinated and compromised to get the coordination solution in pareto optimum. All the programming algorithms are through Matlab, and finally the feasibility and superioirty of this algorithm is proved by a engineering project
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2002
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: IEEE
Date: 2009
Publisher: Springer Berlin Heidelberg
Date: 2014
Publisher: IEEE
Date: 12-2010
Publisher: Acoustical Society of America (ASA)
Date: 09-2017
DOI: 10.1121/1.4999318
Abstract: Ground parrot vocalisation can be considered as an audio event. Test-based erse density multiple instance learning (TB-DD-MIL) is proposed for detecting this event in audio files recorded in the field. The proposed method is motivated by the advantages of multiple instance learning from incomplete training data. Spectral features suitable for encoding the vocal source information of the ground parrot vocalization are also investigated. The proposed method was benchmarked against a dataset collected in various environmental conditions and an audio detection evaluation scheme is proposed. The evaluation includes a study on performance of the various vocal source features and comparison with other classification techniques. Experimental results indicated that the most appropriate feature to encode ground parrot calls is the spectral bandwidth and the proposed TB-DD-MIL method outperformed other existing classification methods.
Publisher: Elsevier BV
Date: 06-2018
Publisher: Elsevier BV
Date: 04-2018
Publisher: IEEE
Date: 12-2010
Publisher: Elsevier BV
Date: 06-2008
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2017
Publisher: IEEE
Date: 10-2005
Publisher: Zhejiang University Press
Date: 12-2012
Publisher: Springer Berlin Heidelberg
Date: 2007
Publisher: Springer Science and Business Media LLC
Date: 18-06-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2015
Publisher: IEEE
Date: 07-2017
Publisher: Elsevier BV
Date: 2014
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2018
Publisher: Springer Science and Business Media LLC
Date: 08-09-2013
Publisher: IEEE
Date: 09-2011
Publisher: IEEE
Date: 07-2019
Publisher: IEEE
Date: 06-2011
Publisher: IEEE
Date: 11-2009
Publisher: Elsevier BV
Date: 11-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2018
Publisher: IEEE
Date: 07-2019
Publisher: IEEE
Date: 12-2016
Publisher: IEEE
Date: 07-2012
DOI: 10.1109/ICME.2012.72
Publisher: ACM
Date: 19-09-2007
Publisher: IEEE
Date: 06-2013
DOI: 10.1109/CVPR.2013.78
Publisher: IEEE
Date: 12-2008
Publisher: IEEE
Date: 09-2018
Publisher: IEEE
Date: 2006
Publisher: Springer Science and Business Media LLC
Date: 10-09-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2020
No related grants have been discovered for Wanqing Li.