Tianbao Zhang

China University of Petroleum, Beijing

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Jiangbo Zhu

Sichuan University

Yongfei Zhu

Hunan Normal University

Hao Zhu

Shanghai Fudan Microelectronics (China)

Lin Chen

Fudan University

Xinwu Pei

Biotechnology Research Institute

Yuping Zhu

Second Military Medical University

Jianfang Bai

Beijing Academy of Agricultural and Forestry Sciences

Zihan Liu

Soochow University

Shaohua Yuan

Zhengzhou University

Xuying Wan

Second Military Medical University

Cooperative Institutions

Chinese Academy of Sciences

Fudan University

Zhejiang University

Institute of High Energy Physics

University of Chinese Academy of Sciences

Shanghai Jiao Tong University

Huazhong University of Science and Technology

Second Military Medical University

Sun Yat-sen University

Sichuan University

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Robust facial landmark detection network based on multiscale attention residual blocks

Lamei Zou Jia Xie Hao Wang Luhan Lu Chengqing Wu

We present a robust facial landmark detection network based on multiscale attention residual blocks (MARBNet) for effectively predicting facial landmark. MARBNet consists of three modules. Firstly, the coarse feature extraction module obtains coarse features through convolution, batch normalization, ReLU activation, and maximum pooling. The fine feature extraction module is composed of 33 multiscale attention residual blocks (MARB). MARB is composed of 1x1 convolution layer, 3x3 convolution layer, 1x1 convolution layer, two multiscale convolution module(MulRes) and channel attention module(CAM). MulRes is used to extract complementary features of different scales, obtain more feature information under different Receptive field, and avoid excessive loss of key information in the input image. CAM enables the network to pay more attention to high-frequency information on the channel, effectively prevents the loss of information, so as to improve the effect of facial landmark detection. The output module consists of two 1x1 convolution layers, one of which outputs landmark heatmap score and landmark coordinate offset, and the other outputs the nearest neighbor landmark offset. The experiment results on WFLW and 300W datasets show that our method is superior to the existing algorithms in terms of normalized mean square error indicators.

Landmark

Convolution (computer science)

Normalization

Feature (linguistics)

10.1117/12.2688423

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Expression of HSP47 in Cleft Palates and Short Limb Malformations,Induced by Retinoic Acid During Mouse Embryogenesis

Carcinogenesis,Teratogenesis and Mutagenesis (2005)

Tianbao Zhang

BACKGROUNDAIM: To study the expression of heat shock protein47(HSP47)in normal forelimbs and short forelimb malformations,normal palates and cleft palates during mouse embryogenesis. MATERIAL AND METHODS: At GD10,gestational mice of the treatment and the control groups were administered with80mg/kg all-trans retinoic acid and the same volume vegetable oil separately.The forelimbs of embryos were harvested in GD11-GD18,and the normal palates and cleft palates were obtained in GD15-GD17.The relative abundance of HSP47of all samples was measured by reverse transcript polymerase chain reaction(RT-PCR). RESULTS: HSP47was expressed in all samples.To the normal forelimbs and short forelimb malformations,with the embryos aging,there was the increasing tendency of the expressional abundance of HSP47in GD11-GD18,their peaks of expression were especially at GD16and GD17,and kept stable in the following age.The expressional abundance of HSP47of the normal palates was stable in GD15-GD17,and the peak of that of the cleft palates was at GD16.The expression of HSP47of the abnormal limbs was stronger than that of the normal limbs in GD11-GD18.The expression of HSP47of the cleft palates has no difference with that of the normal palates in GD15,but it was stronger than that of the cleft palates in GD16-GD17. CONLUSION: The expressional abundance of HSP47in normal limbs and short limb malformations,normal palates and cleft palates induced by all-trans retinoic acid during mouse embryogenesis was increased by stress action.

Forelimb

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Fault Location Scheme of Smart Grid Based on Wireless Sensor Networks

Springer eBooks (2012)

Tianbao Zhang Youling Zhou Bao-Dan Chen

10.1007/978-3-642-29157-9_10

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Evaluation of levamlodipine benzenesulfonate compound I for embryo-fetal developmental toxicity in SD rats and genotoxicity

Reproductive Toxicology (2024)

Yijun Tian Wenjing Shi Fengjiang Liu Huan Li Tianbao Zhang

Developmental toxicity

Ames test

Chromosome aberration

10.1016/j.reprotox.2024.108676

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Investigation on the gene expression profiles of abnormal limb of mouse embryo from exposed dams to MNNG

Huanjing yu zhiye yixue (2005)

Guo Miao-li Jiangbo Zhu Rongfang Chen Tianbao Zhang

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Using a LaBr ₃ :Ce scintillator for positron annihilation lifetime spectroscopy

Chinese Physics C (2012)

刘军辉李道武 Zhiming Zhang 王宝义 Tianbao Zhang

A LaBr3:Ce scintillator has a high light output (～60000 p.e/MeV) and a short decay constant (

Annihilation

Positron Lifetime Spectroscopy

Positron emission

Constant (computer programming)

10.1088/1674-1137/36/4/016

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Citations (6)

Pilot Density Optimization of Simultaneous Energy and Signal Transmission System for Underwater Equipment Based on Channel Estimation

Xueqing Yuan Tianbao Zhang Xiaojun Liang Weitao Zheng

This paper mainly studies the channel characteristics of the simultaneous power line transmission system of underwater equipment, and analyzes the pilot density optimization algorithm used for channel data transmission based on channel estimation, and compares and studies whether the optimization algorithm can optimize the transmission rate of the system in different channel estimation methods. For the analysis of channel characteristics, firstly, the attenuation characteristics of the power line suitable for simultaneous energy and signal transmission in the underwater environment were simulated, and then the load impedance characteristics were added to the circuit for channel modeling. For the pilot density optimization part, according to the pilot classification of IEEE 1901.1 physical layer standard, the blind channel estimation method, the least square method, and the minimum mean square error method are used to estimate the channel, and the channel phase change metric is calculated according to the estimated value, and the pilot level is dynamically adjusted according to the metric threshold table to achieve the most suitable pilot density. Finally, compared with several channel estimation methods, the pilot density optimization algorithm in the channel environment of this paper can improve the data transmission rate of the system under the premise of ensuring a low bit error rate of the system.

10.1109/eeps58791.2023.10256780

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Linear free energy relationship rate constants and basicities of N-substituted phenyl glycines in positronium-glycine complex formation

Chemical Physics Letters (1987)

Chen Rong-Ti Jiachang Liang Youming Du Chun Cao Dinzhen Yin

Positronium

Annihilation

10.1016/0009-2614(87)80236-1

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Homogeneous dual-gate MoS2 field-effect transistors integrated by atomic layer deposition-based film synthesis

Journal of Materials Science Materials in Electronics (2020)

Tao Chen Yang Wang Tianbao Zhang Hao Zhu Lin Chen

Deposition

Nanoelectronics

Electron Mobility

10.1007/s10854-020-03113-3

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A novel density-based clustering method for effective removal of spurious intersections in bearings-only localization

EURASIP Journal on Advances in Signal Processing (2023)

Zhian Deng Zhiguo Wang Tianbao Zhang Chunjie Zhang Weijian Si

Abstract In bearings-only localization, clustering-based methods have been widely used to remove spurious intersections by fusing multiple bearing measurements from different observation stations. Existing clustering methods, including fuzzy C-mean (FCM) clustering and density-based spatial clustering of applications with noise (DBSCAN), must specify the number of clusters and the threshold for defining the neighborhood density, respectively, which are always unknown and difficult to estimate. Moreover, in dense radiation source scenes, existing clustering methods for removal of spurious intersections all deteriorate significantly. Therefore, we propose a novel density-based clustering method called K-M-DBSCAN, which combines the minimum K distance algorithm with Mahalanobis distance-based DBSCAN clustering. Firstly, K-M-DBSCAN uses minimum K distance algorithm for preprocessing to remove most of the spurious intersections and reduce the computational complexity of clustering. Mahalanobis distance-based DBSCAN is used for clustering and spurious intersections recognition. In order to adapt the large variations of sample density in clustering, we use Mahalanobis distance to define an explicit neighborhood of DBSCAN instead of traditional Euclidean distance. Simulation results show that the proposed K-M-DBSCAN performs better than FCM and DBSCAN in removing of spurious intersections.

DBSCAN

Spurious relationship

Mahalanobis distance

10.1186/s13634-023-00974-8

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Citations (5)