Search results for: Linlin Shen

Items from 1 to 20 out of 103 results

article

Hidden Messages: Connotation analysis of Textile Trademarks in the Republic of China (1912-1949)

Tianzhu Cong, Yi Zhang, Linlin Shen, Rongrong Cui

Fibres & Textiles in Eastern Europe > 2023 > Vol. 31, no. 2 > 56--64

This study analyses trademarks of the textile industry issued between 1912–1949 in the Republic of China, revealing the trademarks’ art features and hidden messages. The trademarks’ images and information folders were critically examined within their historical context. The work, by analysing the themes and patterns of the trademarks, revealed that the people-oriented conception, humanistic spirit,...

article

Analysis of Modellings, Techniques and Functions of the Chinese Skullcap

Li Niu, Linlin Shen

Fibres & Textiles in Eastern Europe > 2021 > Vol. 29, no. 5 (149) > 86--90

The Chinese skullcap is a kind of headgear for men specific to China, which prevailed in the dynasties of Ming, Qing and the Republic of China. Its modellings fall into two types: flat-topped and peaked, and its lining is divided into hard and soft to fit the different needs of each season. Through analysis of the physical objects that have remained to this day, it reveals that four types of Chinese...

article

Experimental and numerical study on dynamic mechanical behaviors of low-silver lead-free solder under combined compression-shear loadings

Xiaoyan Niu, Cong Chen, Linlin Shen, Liangbiao Chen, more

Journal of Materials Science: Materials in Electronics > 2019 > 30 > 20 > 18678- 18685

In this paper, the behaviors of low-silver lead-free solder Sn0.3Ag0.7Cu were studied by quasi-static and dynamic compression-shear tests and finite-element analysis. The quasi-static tests were performed on MTS-809 material tester, while the dynamic tests were carried out on a modified split Hopkinson pressure bar (SHPB) system that uses inclined cropped cylinders as incident and transmitter bars...

article

Reverse active learning based atrous DenseNet for pathological image classification

Yuexiang Li, Xinpeng Xie, Linlin Shen, Shaoxiong Liu

BMC Bioinformatics > 2019 > 20 > 1 > 1-15

Background Due to the recent advances in deep learning, this model attracted researchers who have applied it to medical image analysis. However, pathological image analysis based on deep learning networks faces a number of challenges, such as the high resolution (gigapixel) of pathological images and the lack of annotation capabilities. To address these challenges, we propose a training strategy called...

article

An Arrhenius-type constitutive model to predict the deformation behavior of Sn0.3Ag0.7Cu under different temperature

Xiaoyan Niu, Linlin Shen, Cong Chen, Jiang Zhou, more

Journal of Materials Science: Materials in Electronics > 2019 > 30 > 15 > 14611- 14620

Using the fatigue test machine, the isothermal compression of low-silver lead-free solder Sn0.3Ag0.7Cu at the temperature of 40 °C, 80 °C, 120 °C, 160 °C and the strain rate range of 0.0001–0.1 s⁻¹ were studied in this paper. The results show that the flow stress of the material increases with the increase of the strain rate and decreases with the increase of the deformation temperature. The constitutive...

article

Joint Bayesian guided metric learning for end-to-end face verification

Di Chen, Chunyan Xu, Jian Yang, Jianjun Qian, more

Neurocomputing > 2018 > 275 > C > 560-567

In this work, we address the problem of face verification, namely determining whether a pair of face images belongs to the same or different subjects. Previous works often consider solving the problem of face verification in two steps: feature extraction and face recognition, resulting in a fragmented procedure. We argue that these techniques, although working well, fail to explicitly exploit a full...

article

Rotational Invariant Dimensionality Reduction Algorithms

Zhihui Lai, Yong Xu, Jian Yang, Linlin Shen, more

IEEE Transactions on Cybernetics > 2017 > 47 > 11 > 3733 - 3746

A common intrinsic limitation of the traditional subspace learning methods is the sensitivity to the outliers and the image variations of the object since they use the

$\boldsymbol {L_{2}} $

norm as the metric. In this paper, a series of methods based on the

$\boldsymbol {L_{2,1}} $

-norm are proposed for linear dimensionality reduction. Since the

$\boldsymbol {L_{2,1}} $

-norm based objective...

chapter

Multi-way Multi-level Kernel Modeling for Neuroimaging Classification

Lifang He, Chun-Ta Lu, Hao Ding, Shen Wang, more

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) > 6846 - 6854

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

Owing to prominence as a diagnostic tool for probing the neural correlates of cognition, neuroimaging tensor data has been the focus of intense investigation. Although many supervised tensor learning approaches have been proposed, they either cannot capture the nonlinear relationships of tensor data or cannot preserve the complex multi-way structural information. In this paper, we propose a Multi-way...

chapter

Gabor phase feature-based hyperspectral imagery classification

Sen Jia, Huimin Xie, Lin Deng, Linlin Shen

2017 IEEE International Conference on Multimedia and Expo (ICME) > 1291 - 1296

2017 IEEE International Conference on Multimedia and Expo (ICME)

In this paper, a three-dimensional (3D) Gabor phase coding and Hamming distance matching approach, called 3DGPC-HDM, is proposed for hyperspectral imagery classification. Specifically, the Gabor phase features with certain orientations are utilized, which are then encoded by a simple quadrant bit coding scheme. Next, a normalized Hamming distance matching method has been introduced to determine the...

article

HEp-2 Specimen Image Segmentation and Classification Using Very Deep Fully Convolutional Network

Yuexiang Li, Linlin Shen, Shiqi Yu

IEEE Transactions on Medical Imaging > 2017 > 36 > 7 > 1561 - 1572

Reliable identification of Human Epithelial-2 (HEp-2) cell patterns can facilitate the diagnosis of systemic autoimmune diseases. However, traditional approach requires experienced experts to manually recognize the cell patterns, which suffers from the inter-observer variability. In this paper, an automatic pattern recognition system using fully convolutional network (FCN) was proposed to simultaneously...

article

Joint and collaborative representation with local adaptive convolution feature for face recognition with single sample per person

Meng Yang, Xing Wang, Guohang Zeng, Linlin Shen

Pattern Recognition > 2017 > 66 > C > 117-128

With the aid of a universal facial variation dictionary, sparse representation based classifier (SRC) has been naturally extended for face recognition (FR) with single sample per person (SSPP) and achieved promising performance. However, extracting discriminative facial features and building powerful representation framework for classifying query face images are still the bottlenecks of improving...

article

Invariant feature extraction for gait recognition using only one uniform model

Shiqi Yu, Haifeng Chen, Qing Wang, Linlin Shen, more

Neurocomputing > 2017 > 239 > C > 81-93

Gait recognition has been proved useful in human identification at a distance. But many variations such as view, clothing, carrying condition make gait recognition is still challenging in real applications. The variations make it is hard to extract invariant feature to distinguish different subjects. For view variation, one view transformation model can be employed to convert the gait feature from...

chapter

Object specific deep feature and its application to face detection

Xianxu Hou, Jiasong Zhu, Ke Sun, Linlin Shen, more

2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA) > 173 - 176

2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA)

We present a method for exploiting object specific deep features and use face detection as a case study. We seek to discover and exploit the convolutional channels of a CNN in which neurons are activated by the presence of specific objects in the input image. A method for explicitly fine-tuning a pre-trained CNN to induce an object specific channel (OSC) and systematically identifying it for the human...

article

Facial expression synthesis with direction field preservation based mesh deformation and lighting fitting based wrinkle mapping

Weicheng Xie, Linlin Shen, Meng Yang, Jianmin Jiang

Multimedia Tools and Applications > 2018 > 77 > 6 > 7565-7593

Nowadays, facial expression synthesis is widely used in expression simulation, recognition and animation. While a variety of works available in literature are 3D based, these algorithms usually require face matching and trimming, are thus time consuming. In this work, an automatic algorithm for expression synthesis in 2D space is proposed, which mainly consists of three stages.The optimum matching...

chapter

HEp-2 cell classification based on a Deep Autoencoding-Classification convolutional neural network

Jingxin Liu, Bolei Xu, Linlin Shen, Jon Garibaldi, more

2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) > 1019 - 1023

2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)

In this paper, we present a novel deep learning model termed Deep Autoencoding-Classification Network (DACN) for HEp-2 cell classification. The DACN consists of an autoencoder and a normal classification convolutional neural network (CNN), while the two architectures shares the same encoding pipeline. The DACN model is jointly optimized for the classification error and the image reconstruction error...

article

Output Constraint Transfer for Kernelized Correlation Filter in Tracking

Baochang Zhang, Zhigang Li, Xianbin Cao, Qixiang Ye, more

IEEE Transactions on Systems, Man, and Cybernetics: Systems > 2017 > 47 > 4 > 693 - 703

The kernelized correlation filter (KCF) is one of the state-of-the-art object trackers. However, it does not reasonably model the distribution of correlation response during tracking process, which might cause the drifting problem, especially when targets undergo significant appearance changes due to occlusion, camera shaking, and/or deformation. In this paper, we propose an output constraint transfer...

chapter

Deep Feature Consistent Variational Autoencoder

Xianxu Hou, Linlin Shen, Ke Sun, Guoping Qiu

2017 IEEE Winter Conference on Applications of Computer Vision (WACV) > 1133 - 1141

2017 IEEE Winter Conference on Applications of Computer Vision (WACV)

We present a novel method for constructing Variational Autoencoder (VAE). Instead of using pixel-by-pixel loss, we enforce deep feature consistency between the input and the output of a VAE, which ensures the VAE's output to preserve the spatial correlation characteristics of the input, thus leading the output to have a more natural visual appearance and better perceptual quality. Based on recent...

article

A Novel Transient Wrinkle Detection Algorithm and Its Application for Expression Synthesis

Weicheng Xie, Linlin Shen, Jianmin Jiang

IEEE Transactions on Multimedia > 2017 > 19 > 2 > 279 - 292

Because facial wrinkle is a representative feature of facial expression, automatic wrinkle detection has been an important and challenging topic for expression simulation, recognition, and animation. Recently, most works about wrinkle detection have focused on permanent wrinkles (e.g., age wrinkles), which are usually linear shapes, whereas the detection of transient wrinkles (e.g., expression wrinkles)...

article

Joint regularized nearest points for image set based face recognition

Meng Yang, Xing Wang, Weiyang Liu, Linlin Shen

Image and Vision Computing > 2017 > 58 > C > 47-60

Face recognition based on image set has attracted much attention due to its promising performance to overcome various variations. Recently, classifiers of regularized nearest points, including sparse approximated nearest points (SANP), regularized nearest points (RNP) and collaborative regularized nearest points (CRNP), have achieved state-of-the-art performance for image set based face recognition...

article

Structured regularized robust coding for face recognition

Xing Wang, Meng Yang, Linlin Shen

Neurocomputing > 2016 > 216 > C > 18-27

The sparse representation based classifier (SRC) has been successfully applied to robust face recognition (FR) with various variations. To achieve much stronger robustness to facial occlusion, regularized robust coding (RRC) was proposed by designing a new robust representation residual term. Although RRC has achieved the leading performance, it ignores the structured information (i.e., spatial consistence)...

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INFONA - science communication portal

Search results for: Linlin Shen

Hidden Messages: Connotation analysis of Textile Trademarks in the Republic of China (1912-1949)

Analysis of Modellings, Techniques and Functions of the Chinese Skullcap

Experimental and numerical study on dynamic mechanical behaviors of low-silver lead-free solder under combined compression-shear loadings

Reverse active learning based atrous DenseNet for pathological image classification

An Arrhenius-type constitutive model to predict the deformation behavior of Sn0.3Ag0.7Cu under different temperature

Joint Bayesian guided metric learning for end-to-end face verification

Rotational Invariant Dimensionality Reduction Algorithms

Multi-way Multi-level Kernel Modeling for Neuroimaging Classification

Gabor phase feature-based hyperspectral imagery classification

HEp-2 Specimen Image Segmentation and Classification Using Very Deep Fully Convolutional Network

Joint and collaborative representation with local adaptive convolution feature for face recognition with single sample per person

Invariant feature extraction for gait recognition using only one uniform model

Object specific deep feature and its application to face detection

Facial expression synthesis with direction field preservation based mesh deformation and lighting fitting based wrinkle mapping

HEp-2 cell classification based on a Deep Autoencoding-Classification convolutional neural network

Output Constraint Transfer for Kernelized Correlation Filter in Tracking

Deep Feature Consistent Variational Autoencoder

A Novel Transient Wrinkle Detection Algorithm and Its Application for Expression Synthesis

Joint regularized nearest points for image set based face recognition

Structured regularized robust coding for face recognition

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