Nanning Zheng

artykuł

Detection of thin‐cap fibroatheroma in IVOCT images based on weakly supervised learning and domain knowledge

Peiwen Shi, Jingmin Xin, Jiayi Wu, Yangyang Deng, więcej

Journal of Biophotonics > 16 > 5 > n/a - n/a

Automatic detection of thin‐cap fibroatheroma (TCFA) on intravascular optical coherence tomography images is essential for the prevention of acute coronary syndrome. However, existing methods need to mark the exact location of TCFAs on each frame as supervision, which is extremely time‐consuming and expensive. Hence, a new weakly supervised framework is proposed to detect TCFAs using only image‐level...

artykuł

Autonomous driving: cognitive construction and situation understanding

Shitao Chen, Zhiqiang Jian, Yuhao Huang, Yu Chen, więcej

Science China Information Sciences > 2019 > 62 > 8 > 1-27

Autonomous vehicle is a kind of typical complex artificial intelligence system. In current research of autonomous driving, the most widely adopted technique is to use a basic framework of serial information processing and computations, which consists of four modules: perception, planning, decision-making, and control. However, this framework based on data-driven computing performs low computational...

artykuł

Cross multivariate correlation coefficients as screening tool for analysis of concurrent EEG‐fMRI recordings

Hong Ji, Nathan M. Petro, Badong Chen, Zejian Yuan, więcej

Journal of Neuroscience Research > 96 > 7 > 1159 - 1175

Over the past decade, the simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) data has garnered growing interest because it may provide an avenue towards combining the strengths of both imaging modalities. Given their pronounced differences in temporal and spatial statistics, the combination of EEG and fMRI data is however methodologically challenging...

artykuł

Deep self-paced learning for person re-identification

Sanping Zhou, Jinjun Wang, Deyu Meng, Xiaomeng Xin, więcej

Pattern Recognition > 2018 > 76 > C > 739-751

Person re-identification (Re-ID) usually suffers from noisy samples with background clutter and mutual occlusion, which makes it extremely difficult to distinguish different individuals across the disjoint camera views. In this paper, we propose a novel deep self-paced learning (DSPL) algorithm to alleviate this problem, in which we apply a self-paced constraint and symmetric regularization to help...

artykuł

Managing Battery Aging for High Energy Availability in Green Datacenters

Longjun Liu, Hongbin Sun, Chao Li, Tao Li, więcej

IEEE Transactions on Parallel and Distributed Systems > 2017 > 28 > 12 > 3521 - 3536

Energy storage devices (ESD), such as UPS batteries, have been repurposed in datacenter as a promising tuning knob for peak power shaving and power cost reducing. However, batteries progressively aging due to irregular usage patterns, which result in less effective capacity and even pose serious threat to server availability. Nevertheless, prior proposals largely ignore the aging issues of battery...

artykuł

A Novel Method of Minimizing View Synthesis Distortion Based on Its Non-Monotonicity in 3D Video

Meng Yang, Nanning Zheng, Ce Zhu, Fei Wang

IEEE Transactions on Image Processing > 2017 > 26 > 11 > 5122 - 5137

In depth-based 3D video, the view synthesis distortion (VSD), is generally measured by modeling the effect of texture and depth errors separately. With such a development, it has been referred that the VSD changes monotonically with respect to to both the texture and depth distortions. In this paper, we find that the VSD does not always change monotonically with them by both theoretical analysis and...

rozdział

View Adaptive Recurrent Neural Networks for High Performance Human Action Recognition from Skeleton Data

Pengfei Zhang, Cuiling Lan, Junliang Xing, Wenjun Zeng, więcej

2017 IEEE International Conference on Computer Vision (ICCV) > 2136 - 2145

2017 IEEE International Conference on Computer Vision (ICCV)

Skeleton-based human action recognition has recently attracted increasing attention due to the popularity of 3D skeleton data. One main challenge lies in the large view variations in captured human actions. We propose a novel view adaptation scheme to automatically regulate observation viewpoints during the occurrence of an action. Rather than re-positioning the skeletons based on a human defined...

artykuł

Video Object Discovery and Co-Segmentation with Extremely Weak Supervision

Le Wang, Gang Hua, Rahul Sukthankar, Jianru Xue, więcej

IEEE Transactions on Pattern Analysis and Machine Intelligence > 2017 > 39 > 10 > 2074 - 2088

We present a spatio-temporal energy minimization formulation for simultaneous video object discovery and co-segmentation across multiple videos containing irrelevant frames. Our approach overcomes a limitation that most existing video co-segmentation methods possess, i.e., they perform poorly when dealing with practical videos in which the target objects are not present in many frames. Our formulation...

rozdział

Direction-of-arrival estimation of coherent narrowband signals with arbitrary linear array

Xiao Chen, Jingmin Xin, Nanning Zheng, Akira Sano

2017 IEEE International Workshop on Signal Processing Systems (SiPS) > 1 - 5

2017 IEEE International Workshop on Signal Processing Systems (SiPS)

In this paper, we consider the direction-of-arrivals (DOAs) estimation of coherent narrowband signals impinging on an arbitrary linear array in a computational efficient way. A new interpolation transform based modified Capon beam-forming method is proposed without eigendecomposition, where the arbitrary linear array is transformed to a virtual uniform linear array (ULA) by utilizing the interpolation...

rozdział

A rehabilitation gait training system for half lower limb disorder

Siyang Han, Hengxing Zhang, Xiao Wang, Linhai Xu, więcej

2017 Chinese Automation Congress (CAC) > 3841 - 3847

2017 Chinese Automation Congress (CAC)

Gait training is one of main means of rehabilitation of lower limb disfunction. Nevertheless, the promotion of clinical gait training is inhibited by the professional skill and labor consumption of physiatrist. It is with great practical value to design an automatic rehabilitation equipment which could increase the effectiveness and quality of training progress, meanwhile reduce labor costs. In this...

artykuł

Automatic salient object sequence rebuilding for video segment analysis

Tie Liu, Haibin Duan, Yuanyuan Shang, Zejian Yuan, więcej

Science China Information Sciences > 2018 > 61 > 1 > 1-12

Detection of salient object sequences from video data is challenging when the salient object changes between consecutive frames. In this study, we addressed the salient object sequence rebuilding problem with video segment analysis. We reformulated the problem as a binary labeling problem, analyzed the potential salient object sequences in the video using a clustering method, and separated the salient...

artykuł

Balanced Mixture of Deformable Part Models With Automatic Part Configurations

De Cheng, Yihong Gong, Jingjun Wang, Nanning Zheng

IEEE Transactions on Circuits and Systems for Video Technology > 2017 > 27 > 9 > 1962 - 1973

This paper presents a method to improve the traditional mixture of deformable part models (MDPM) method from the learning perspective. First, an object part configuration learning algorithm based on group sparsity constraint is introduced to automatically discover the object part number, size, and location. The algorithm imposes two additional regularization terms in addition to the standard hinge...

rozdział

POSTER: Accelerate GPU Concurrent Kernel Execution by Mitigating Memory Pipeline Stalls

Hongwen Dai, Zhen Lin, Chao Li, Chen Zhao, więcej

2017 26th International Conference on Parallel Architectures and Compilation Techniques (PACT) > 144 - 145

2017 26th International Conference on Parallel Architectures and Compilation Techniques (PACT)

In this study, we demonstrate that the performance may be undermined in the state-of-the-art intra-SM sharing schemes for concurrent kernel execution (CKE) on GPUs, due to the interference among concurrent kernels. We highlight that cache partitioning techniques proposed for CPUs are not effective for GPUs. Then we propose to balance memory accesses and limit the number of inflight memory instructions...

rozdział

Correntropy induced metric based common spatial patterns

Jiyao Dong, Badong Chen, Na Lu, Haixian Wang, więcej

2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP) > 1 - 6

2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP)

Common spatial patterns (CSP) is a widely used method in the field of electroencephalogram (EEG) signal processing. The goal of CSP is to find spatial filters that maximize the ratio between the variances of two classes. The conventional CSP is however sensitive to outliers because it is based on the L₂-norm. Inspired by the correntropy induced metric (CIM), we propose in this work a new algorithm,...

artykuł

Correntropy Maximization via ADMM: Application to Robust Hyperspectral Unmixing

Fei Zhu, Abderrahim Halimi, Paul Honeine, Badong Chen, więcej

IEEE Transactions on Geoscience and Remote Sensing > 2017 > 55 > 9 > 4944 - 4955

In hyperspectral images, some spectral bands suffer from low signal-to-noise ratio due to noisy acquisition and atmospheric effects, thus requiring robust techniques for the unmixing problem. This paper presents a robust supervised spectral unmixing approach for hyperspectral images. The robustness is achieved by writing the unmixing problem as the maximization of the correntropy criterion subject...

rozdział

Iteratively Multiple Projections Optimization for Product Quantization in Nearest Neighbor Search

Jin Li, Xuguang Lan, Nanning Zheng

2017 IEEE International Conference on Big Knowledge (ICBK) > 65 - 71

2017 IEEE International Conference on Big Knowledge (ICBK)

Recently, the variable length coding product quantization is proposed to accelerate the speed of codebook training for approximate nearest neighbor (ANN) search. And the Gaussian Mixture model (GMM) is trained as a coarse quantizer to project the data into different subspaces respectively. However, the existing method trains the GMM without considering the quantization distortion. In this paper, we...

artykuł

Parallel vision for perception and understanding of complex scenes: methods, framework, and perspectives

Kunfeng Wang, Chao Gou, Nanning Zheng, James M. Rehg, więcej

Artificial Intelligence Review > 2017 > 48 > 3 > 299-329

In the study of image and vision computing, the generalization capability of an algorithm often determines whether it is able to work well in complex scenes. The goal of this review article is to survey the use of photorealistic image synthesis methods in addressing the problems of visual perception and understanding. Currently, the ACP Methodology comprising artificial systems, computational experiments,...

rozdział

ER3: A Unified Framework for Event Retrieval, Recognition and Recounting

Zhanning Gao, Gang Hua, Dongqing Zhang, Nebojsa Jojic, więcej

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) > 2107 - 2116

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

We develop a unified framework for complex event retrieval, recognition and recounting. The framework is based on a compact video representation that exploits the temporal correlations in image features. Our feature alignment procedure identifies and removes the feature redundancies across frames and outputs an intermediate tensor representation we call video imprint. The video imprint is then fed...

rozdział

Point to Set Similarity Based Deep Feature Learning for Person Re-Identification

Sanping Zhou, Jinjun Wang, Jiayun Wang, Yihong Gong, więcej

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) > 5028 - 5037

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Person re-identification (Re-ID) remains a challenging problem due to significant appearance changes caused by variations in view angle, background clutter, illumination condition and mutual occlusion. To address these issues, conventional methods usually focus on proposing robust feature representation or learning metric transformation based on pairwise similarity, using Fisher-type criterion. The...

artykuł

A new compressive sensing video coding framework based on Gaussian mixture model

Xiangwei Li, Xuguang Lan, Meng Yang, Jianru Xue, więcej

Signal Processing: Image Communication > 2017 > 55 > C > 66-79

In this paper, we specifically design an efficient compressive sensing video (CSV) coding framework for the CSV system, by considering the distribution characteristics of the CSV frame. To explore the spatial redundancy of the CSV, the CSV frame is first divided into blocks and each block is modeled by a Gaussian mixture model (GMM), and then it is compressed by a product vector quantization. We further...

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Wyniki wyszukiwania dla: Nanning Zheng

Detection of thin‐cap fibroatheroma in IVOCT images based on weakly supervised learning and domain knowledge

Autonomous driving: cognitive construction and situation understanding

Cross multivariate correlation coefficients as screening tool for analysis of concurrent EEG‐fMRI recordings

Deep self-paced learning for person re-identification

Managing Battery Aging for High Energy Availability in Green Datacenters

A Novel Method of Minimizing View Synthesis Distortion Based on Its Non-Monotonicity in 3D Video

View Adaptive Recurrent Neural Networks for High Performance Human Action Recognition from Skeleton Data

Video Object Discovery and Co-Segmentation with Extremely Weak Supervision

Direction-of-arrival estimation of coherent narrowband signals with arbitrary linear array

A rehabilitation gait training system for half lower limb disorder

Automatic salient object sequence rebuilding for video segment analysis

Balanced Mixture of Deformable Part Models With Automatic Part Configurations

POSTER: Accelerate GPU Concurrent Kernel Execution by Mitigating Memory Pipeline Stalls

Correntropy induced metric based common spatial patterns

Correntropy Maximization via ADMM: Application to Robust Hyperspectral Unmixing

Iteratively Multiple Projections Optimization for Product Quantization in Nearest Neighbor Search

Parallel vision for perception and understanding of complex scenes: methods, framework, and perspectives

ER3: A Unified Framework for Event Retrieval, Recognition and Recounting

Point to Set Similarity Based Deep Feature Learning for Person Re-Identification

A new compressive sensing video coding framework based on Gaussian mixture model

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