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463 results on '"Gao, Mingliang"'

9. Frequency-Spatial Feature Fusion Network for Infrared and Visible Image Fusion

Author

Song, Wenhao, Gao, Mingliang, Li, Qilei, Jeon, Gwanggil, Camacho, David, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Nguyen, Ngoc Thanh, editor, Huynh, Cong-Phap, editor, Nguyen, Thanh Thuy, editor, Le-Khac, Nhien-An, editor, and Nguyen, Quang-Vu, editor

Published
2024
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10. An Efficient Server Lid Detection System Based on Sound Recognition and Deep Learning

Author

Gao, Mingliang, Fu, Changzhao, Gao, Shan, Tang, Yu, Lu, Rongqin, Sun, Yi, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, and S. Shmaliy, Yuriy, editor

Published
2024
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11. Predictive Maintenance System and Method Based on Smart Edge Gateways

Author

Gao, Mingliang, Wu, Jianguo, Gao, Shan, Tang, Yu, Wei, Ran, Sun, Hongliang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, and S. Shmaliy, Yuriy, editor

Published
2024
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12. PHM Fault Diagnosis Algorithms, Devices and Systems Based on Edge Computing with Quantum Genetic Algorithm Optimised XGBoost

Author

Gao, Mingliang, Fu, Changzhao, Gao, Shan, Tang, Yu, Wu, Jianguo, Sun, Yi, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, and S. Shmaliy, Yuriy, editor

Published
2024
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33. A Symmetric Encoder-Decoder with Residual Block for Infrared and Visible Image Fusion

Author

Jian, Lihua, Yang, Xiaomin, Liu, Zheng, Jeon, Gwanggil, Gao, Mingliang, and Chisholm, David

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

In computer vision and image processing tasks, image fusion has evolved into an attractive research field. However, recent existing image fusion methods are mostly built on pixel-level operations, which may produce unacceptable artifacts and are time-consuming. In this paper, a symmetric encoder-decoder with a residual block (SEDR) for infrared and visible image fusion is proposed. For the training stage, the SEDR network is trained with a new dataset to obtain a fixed feature extractor. For the fusion stage, first, the trained model is utilized to extract the intermediate features and compensation features of two source images. Then, extracted intermediate features are used to generate two attention maps, which are multiplied to the input features for refinement. In addition, the compensation features generated by the first two convolutional layers are merged and passed to the corresponding deconvolutional layers. At last, the refined features are fused for decoding to reconstruct the final fused image. Experimental results demonstrate that the proposed fusion method (named as SEDRFuse) outperforms the state-of-the-art fusion methods in terms of both subjective and objective evaluations.

Published
2019

37. Electric Transformer Oil Leakage Visual Detection as Service Based on LSTM and Genetic Algorithm

Author

Gao, Mingliang, Zhang, Cihang, Xu, Chongyao, Gao, Qi, Gao, Jiwei, Yan, Jing, Liu, Weidong, Fan, Xiaohu, Tu, Hao, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Tekinerdogan, Bedir, editor, Wang, Yingwei, editor, and Zhang, Liang-Jie, editor

Published
2022
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50. Exploring the Effects of Irrigation Schedules on Evapotranspiration Partitioning and Crop Water Productivity of Winter Wheat (Triticum aestivum L.) in North China Plain Using RZWQM2.

Author

Gao, Mingliang, Liu, Fuying, Zhang, Haoze, Yuan, Huabin, Zong, Rui, Zhang, Mingming, and Li, Quanqi

Subjects
*IRRIGATION scheduling, *WHEAT, *WATER shortages, *GRAIN yields, *INVESTIGATIONAL therapies
Abstract

A significant basis for winter wheat production in China is the North China Plain (NCP). However, winter wheat production is severely hampered by water shortages in this area. Transpiration co‐occurs with photosynthesis, affecting crop water productivity (CWP). The purpose of this experiment is to use Root Zone Water Quality Model (RZWQM2) to study actual transpiration (AT) and evaporation (AE) under different irrigation schedules and then determine its impact on grain yield and CWP. In the 2019–2022 winter wheat growing seasons, four experimental treatments were set up: no irrigation during growth period (I0), irrigation at jointing stage (I1), irrigation at jointing and anthesis stage (I2) and irrigation at jointing, anthesis and filling stage (I3), and the RZWQM2 model was calibrated and verified in this experiment. A higher yield (7840.90 kg/ha for an average of 3 years) and the highest CWP can be obtained in I2 treatment (increased by 12.72%, 5.98% and 4.28% for an average of 3 years, respectively, compared to the other three treatments). The model has a good simulation effect on soil water dynamic change and plant physiological performance of the four treatments; the model showed that irrigation increased the simulated AE and AT; however, reduced AE/actual evapotranspiration. For the whole growth period, AT in I3, I2, I1 and I0 was 351.70, 317.30, 271.50 and 223.70 mm, respectively. Especially in the late growth stage of winter wheat, the AT in I3 was 65.20 mm for an average of 3 years, which was significantly higher than I2, I1 and I0 by 31.60, 13.50 and 10.00 mm, respectively. Thus, I3 increased AT at the late growth stage of winter wheat and resulted in an increase in grain yield; however, it did not significantly increase CWP. This study demonstrated that irrigation at winter wheat jointing and anthesis stages can improve the CWP to achieve the goal of stable grain yield and water saving. [ABSTRACT FROM AUTHOR]

Published
2024
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