Jun Chu

Moscow State University

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i-10 index

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Co-Authors

Jun Miao

Nanchang Hangkong University

Lu Leng

Nanchang Hangkong University

L.B. Tong

Xi'an University of Architecture and Technology

De Ning Zou

Xi'an University of Architecture and Technology

Guimei Zhang

First Hospital of Jilin University

Lingfeng Wang

Beijing University of Chemical Technology

S. Kamado

Nagaoka University of Technology

Kai Huang

Nanchang Hangkong University

Hongjie Zhang

Changchun Institute of Applied Chemistry

Z.H. Jiang

Jilin University

Cooperative Institutions

Nanchang Hangkong University

Chinese Academy of Sciences

Shanghai Jiao Tong University

Zhengzhou University

Xi'an University of Architecture and Technology

University of Chinese Academy of Sciences

University at Buffalo, State University of New York

Harbin Institute of Technology

Nanchang University

Jilin University

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Binocular stereo vision system design for lunar rover

Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (2007)

Jun Chu Chunlin Jiao Hang Guo Xiaoyu Zhang

In this paper, we integrate a pair of CCD cameras and a digital pan/title of two degrees of freedom into a binocular stereo vision system, which simulates the panoramic cameras system of the lunar rover. The constraints for placement and parameters choice of the stereo cameras pair are proposed based on science objective of Chang'e-IImission. And then these constraints are applied to our binocular stereo vision system and analyzed the location precise of it. Simulation and experimental result confirm the constraints proposed and the analysis of the location precise.

Stereo cameras

Computer stereo vision

Binocular disparity

Machine Vision

10.1117/12.743159

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Citations (2)

Remote Sensing Image Retrieval by Multi-Scale Attention-Based CNN and Product Quantization

Jun Chu Linhao Li Xiaowu Xiao

With the development of information technology, all kinds of image information are expanding. It has been a hot issue in computer vision to quickly retrieval interested images from data sets. The complexity of remote sensing images brings new challenges to the retrieval process. This paper presents a new method for remote sensing image retrieval. In our proposed multi-scale attention-based convolutional neural network with improved product quantization method (APQ), we first use deep neural network with visual attention mechanism to extract feature representation of remote sensing images, and then we use an improved product quantization method to reduce the dimension of the features for the purpose of reducing the retrieval computation cost. Experiments on two remote sensing datasets Satellite Remote Sensing and NWPU show that our APQ method can outperform some state-of-the-art remote sensing image retrieval methods.

10.23919/ccc52363.2021.9549732

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Citations (3)

Structural optimization of intake pipe based on pulsation

Jun Chu Yi Zhang

The paper studied on a 125cc single-cylinder gasoline engine. Within the range of engine economical rotational speed, optimized structure of intake pipe can arouse airflow of inertial and resonant effect. The theoretical model analysis and computer simulation provides directional guidance of improving intake system, which may reduce test cost and shorten the redesign cycle. Through the experiment of speed characteristic on dynamometer bench, test data of original and improved intake pipes were compared. Both theoretical models and experimental results show that the effective use of intake pulsation can improve the engine power performance and fuel economy.

Dynamometer

Test bench

10.1109/emeit.2011.6023050

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Citations (0)

Scene classification based on SIFT combined with GIST

International Conference on Information Science, Electronics and Electrical Engineering (2014)

Jun Chu Guihua Zhao

To overcome the disadvantage of global GIST features that lose local information needed for scene classification tasks, a new scene feature description method that combines global GIST with local SIFT features is proposed in this paper. Firstly, local context information and global RGB color quantization information are introduced into the traditional SIFT and GIST features respectively, and then the similarity between the characteristics of the scene is measured based on BOW (Bag Of Words). Finally, the scene classification task is performed with SVM. The influence on classification accuracy of the combined features with different SVM match kernels and BOW is investigated in experiment, and based on three scene datasets, the classification results of the combined feature are compared with that of the methods in literature based on single feature of global GIST or local SIFT, the experimental results show the efficiency of the proposed feature construction method.

Scale-invariant feature transform

Feature (linguistics)

RGB color model

10.1109/infoseee.2014.6948126

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Citations (8)

Simultaneously Enhanced Mechanical Properties and Damping Capacities of ZK60 Mg Alloys Processed by Multi-Directional Forging

Acta Metallurgica Sinica (English Letters) (2020)

Libo Tong Jun Chu De Ning Zou Qi Sun S. Kamado

Equiaxed crystals

Texture (cosmology)

Dynamic Recrystallization