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Le An
University of North Carolina at Chapel Hill
69Publications
18H-index
973Citations
Publications 67
Newest
#1Jialin Peng (UNC: University of North Carolina at Chapel Hill)H-Index: 7
#2Xiaofeng Zhu (UNC: University of North Carolina at Chapel Hill)H-Index: 48
Last.Dou Shen (UNC: University of North Carolina at Chapel Hill)H-Index: 84
view all 5 authors...
Abstract Multimodal data fusion has shown great advantages in uncovering information that could be overlooked by using single modality. In this paper, we consider the integration of high-dimensional multi-modality imaging and genetic data for Alzheimer’s disease (AD) diagnosis. With a focus on taking advantage of both phenotype and genotype information, a novel structured sparsity, defined by l1, p-norm (p > 1), regularized multiple kernel learning method is designed. Specifically, to facilitate...
3 CitationsSource
#1Ehsan Adeli (Stanford University)H-Index: 11
#2Kim-Han Thung (UNC: University of North Carolina at Chapel Hill)H-Index: 14
Last.Dou Shen (UNC: University of North Carolina at Chapel Hill)H-Index: 84
view all 7 authors...
Discriminative methods commonly produce models with relatively good generalization abilities. However, this advantage is challenged in real-world applications (e.g., medical image analysis problems), in which there often exist outlier data points ( sample-outliers ) and noises in the predictor values ( feature-noises ). Methods robust to both types of these deviations are somewhat overlooked in the literature. We further argue that denoising can be more effective, if we learn the model using all...
6 CitationsSource
#1Le An (HUST: Huazhong University of Science and Technology)H-Index: 18
#2Zhen Qin (UCR: University of California, Riverside)H-Index: 7
Last.Songfan Yang (Sichuan University)H-Index: 12
view all 4 authors...
Matching people in different cameras, commonly referred to as person re-identification, is a challenging task. The challenges come from the drastic appearance variation across different camera views caused by changes in pose, lighting condition, occlusion, background, and so on. Instead of matching images in the original feature space, many existing methods learn distance metrics or feature transformations to improve the matching accuracy. For example, data from different camera views can be pro...
5 CitationsSource
#1Lei Xiang (SJTU: Shanghai Jiao Tong University)H-Index: 7
#2Yu QiaoH-Index: 42
Last.Dou Shen (KU: Korea University)H-Index: 84
view all 7 authors...
Positron emission tomography (PET) is an essential technique in many clinical applications such as tumor detection and brain disorder diagnosis. In order to obtain high-quality PET images, a standard-dose radioactive tracer is needed, which inevitably causes the risk of radiation exposure damage. For reducing the patient's exposure to radiation and maintaining the high quality of PET images, in this paper, we propose a deep learning architecture to estimate the high-quality standard-dose PET (SP...
34 CitationsSource
#1Le An (HUST: Huazhong University of Science and Technology)H-Index: 18
#2Xiaojing Chen (UCR: University of California, Riverside)H-Index: 7
Last.Xuelong Li (CAS: Chinese Academy of Sciences)H-Index: 82
view all 4 authors...
Matching people across nonoverlapping cameras, also known as person re-identification, is an important and challenging research topic. Despite its great demand in many crucial applications such as surveillance, person re-identification is still far from being solved. Due to drastic view changes, even the same person may look quite dissimilar in different cameras. Illumination and pose variations further aggravate this discrepancy. To this end, various feature descriptors have been designed for i...
6 CitationsSource
#1Jun Zhang (UNC: University of North Carolina at Chapel Hill)H-Index: 13
#2Mingxia Liu (UNC: University of North Carolina at Chapel Hill)H-Index: 16
Last.Dou Shen (UNC: University of North Carolina at Chapel Hill)H-Index: 84
view all 5 authors...
Structural magnetic resonance imaging (MRI) has been proven to be an effective tool for Alzheimer's disease (AD) diagnosis. While conventional MRI-based AD diagnosis typically uses images acquired at a single time point, a longitudinal study is more sensitive in detecting early pathological changes of AD, making it more favorable for accurate diagnosis. In general, there are two challenges faced in MRI-based diagnosis. First, extracting features from structural MR images requires time-consuming ...
25 CitationsSource
#1Le An (HUST: Huazhong University of Science and Technology)H-Index: 18
#2Xiaojing Chen (UCR: University of California, Riverside)H-Index: 7
Last.Songfan Yang (Sichuan University)H-Index: 12
view all 3 authors...
Abstract Person re-identification refers to the task of matching people in non-overlapping cameras. As the concerns for public safety keep rising, the ability to accurately identify a subject in surveillance cameras is a highly demanded technique. In practice, person re-identification is challenging due to the substantial appearance shift caused by view change. Many factors, such as illumination, pose, and image quality, can affect the matching accuracy. In the past, many feature descriptors hav...
5 CitationsSource
#1Zhixing Jin (UCR: University of California, Riverside)H-Index: 11
#2Le An (HUST: Huazhong University of Science and Technology)H-Index: 18
Last.Bir Bhanu (UCR: University of California, Riverside)H-Index: 47
view all 3 authors...
Pedestrian tracking in video has been a popular research topic with many practical applications. In order to improve tracking performance, many ideas have been proposed, among which the use of geometric information is one of the most popular directions in recent research. In this paper, we propose a novel multicamera pedestrian tracking framework, which incorporates the structural information of pedestrian groups in the crowd. In this framework, first, a new cross-camera model is proposed, which...
3 CitationsSource
#1Qiong Liu (HUST: Huazhong University of Science and Technology)H-Index: 11
#2Yang Li (Beihang University)H-Index: 17
Last.Yi Zhen (LinkedIn)H-Index: 11
view all 4 authors...
Source
#1Renping Yu (Nanjing University of Science and Technology)H-Index: 2
#2Hong-Ying Zhang (UNC: University of North Carolina at Chapel Hill)H-Index: 28
Last.Dou ShenH-Index: 84
view all 6 authors...
Brain functional network analysis has shown great potential in understanding brain functions and also in identifying biomarkers for brain diseases, such as Alzheimer's disease (AD) and its early stage, mild cognitive impairment (MCI). In these applications, accurate construction of biologically meaningful brain network is critical. Sparse learning has been widely used for brain network construction; however, its l1-norm penalty simply penalizes each edge of a brain network equally, without consi...
24 CitationsSource
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