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Bobo Ju - IEEE Xplore Author Profile

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Author details

Bobo Ju

Publications

3

Citations

106

Publications by Year

20192020

Co-Authors:

Hongyan LiXuefeng LiangXiao LinYan WuChunxue Wu

Show All Co-Authors (9)

Bobo Ju

Affiliation

School of Optical-Electrical and Computer Engineering

University of Shanghai for Science and Technology

Shanghai, China

Publication Topics

Complex Disaster,
Convolutional Neural Network,
Deep Learning,
Neural Network,
Action-value Function,
Actual Values,
Adam Optimization Algorithm,
AlphaGo,
Average Reward,
Beginning Of Training,
Binary Image,
Binary Map

Biography

Bobo Ju is currently pursuing the master’s degree in computer science and technology with the University of Shanghai for Science and Technology. He is also engaged in big data and artificial intelligence research under the guidance of Prof. C. Wu.(Based on document published on 14 January 2020).

Publications

3

Citations

106

Publications by Year

20192020

Co-Authors:

Hongyan Li
Xuefeng Liang
Xiao Lin
Yan Wu
Chunxue Wu

Show All Co-Authors (9)

Author's Published Works

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Showing 1-3 of 3 results

Journals (2)

Conferences (1)

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Chunxue Wu(3)
Bobo Ju(3)
Naixue Xiong(3)
Yan Wu(3)
Xuefeng Liang(1)
College of Intelligence and Computing, Tianjin University, Tianjin, China(2)
School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China(2)
State Key Laboratory for Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, China(1)
O’Neill School of Public and Environmental Affairs, Indiana University Bloomington, Bloomington, USA(1)
Department of Mathematics and Computer Science, Northeastern State University, Tahlequah, USA(1)
IEEE Access(2)
2019 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW)(1)
IEEE(3)
Yilan, Taiwan(1)
Complex Disaster(2)
Convolutional Neural Network(2)
Deep Learning(2)
Neural Network(2)
Action-value Function(1)

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SlimRGBD: A Geographic Information Photography Noise Reduction System for Aerial Remote Sensing

Chunxue Wu;Bobo Ju;Yan Wu;Naixue Xiong

Year: 2020 | Volume: 8 | Journal Article |

Cited by: Papers (6)

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In the past ten years, civil drone technology has developed rapidly, and UAV (Unmanned Aerial Vehicle) has been widely used in various industries. Especially in the field of aerial remote sensing, the emergence of UAV technology has enabled the geographical information of remote areas that are not concerned to be quickly presented. However, UAV aerial photography is greatly affected by the weather...Show More

SlimRGBD: A Geographic Information Photography Noise Reduction System for Aerial Remote Sensing

Chunxue Wu;Bobo Ju;Yan Wu;Naixue Xiong

Year: 2020 | Volume: 8 | Journal Article |

River Blocking Judgment Based on Color Constancy Color Similarity Measure under Complex Disasters

Chunxue Wu;Bobo Ju;Guisong Yang;Yan Wu;Hongming Yang;Naixue Xiong

2019 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW)

Year: 2019 | Conference Paper |

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This paper analyzes the map formed by aerial photography of drones, and uses the color constancy color similarity measure CCCI and binary image similarity measure to judge whether the river is blocked and the degree of blockage, instead of the previous artificial judgment on the barrier lake. The results show that the CCCI water body extraction method is less affected by the mountain shadow and th...Show More

River Blocking Judgment Based on Color Constancy Color Similarity Measure under Complex Disasters

Chunxue Wu;Bobo Ju;Guisong Yang;Yan Wu;Hongming Yang;Naixue Xiong

2019 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW)

Year: 2019 | Conference Paper |

UAV Autonomous Target Search Based on Deep Reinforcement Learning in Complex Disaster Scene

Chunxue Wu;Bobo Ju;Yan Wu;Xiao Lin;Naixue Xiong;Guangquan Xu;Hongyan Li;Xuefeng Liang

Year: 2019 | Volume: 7 | Journal Article |

Cited by: Papers (100)

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In recent years, artificial intelligence has played an increasingly important role in the field of automated control of drones. After AlphaGo used Intensive Learning to defeat the World Go Championship, intensive learning gained widespread attention. However, most of the existing reinforcement learning is applied in games with only two or three moving directions. This paper proves that deep reinfo...Show More

UAV Autonomous Target Search Based on Deep Reinforcement Learning in Complex Disaster Scene

Chunxue Wu;Bobo Ju;Yan Wu;Xiao Lin;Naixue Xiong;Guangquan Xu;Hongyan Li;Xuefeng Liang

Year: 2019 | Volume: 7 | Journal Article |

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