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3. Infrared and Visible Image Fusion with ResNet and zero-phase component analysis

Author

Li, Hui, Wu, Xiao-Jun, and Durrani, Tariq S.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Feature extraction and processing tasks play a key role in Image Fusion, and the fusion performance is directly affected by the different features and processing methods undertaken. By contrast, most of deep learning-based methods use deep features directly without feature extraction or processing. This leads to the fusion performance degradation in some cases. To solve these drawbacks, we propose a deep features and zero-phase component analysis (ZCA) based novel fusion framework is this paper. Firstly, the residual network (ResNet) is used to extract deep features from source images. Then ZCA is utilized to normalize the deep features and obtain initial weight maps. The final weight maps are obtained by employing a soft-max operation in association with the initial weight maps. Finally, the fused image is reconstructed using a weighted-averaging strategy. Compared with the existing fusion methods, experimental results demonstrate that the proposed framework achieves better performance in both objective assessment and visual quality. The code of our fusion algorithm is available at https://github.com/hli1221/imagefusion_resnet50, Comment: 22pages, 9 figures, 7 tables

Published
2018
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4. Introduction

Author

Durrani, Tariq S., Wang, Wei, Forbes, Sheila M, Durrani, Tariq S., editor, Wang, Wei, editor, and Forbes, Sheila M, editor

Published
2019
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7. Pedestrian Retrieval Using Valuable Absence Augmentation

Author

Hao, Xiaolong, Liu, Shuang, Zhang, Zhong, Durrani, Tariq S., Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, 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, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, 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, Zhang, Junjie James, Series Editor, Wang, Wei, editor, Mu, Jiasong, editor, Liu, Xin, editor, Na, Zhenyu, editor, and Chen, Bingcai, editor

Published
2020
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8. Evaluation Distance Metrics for Pedestrian Retrieval

Author

Zhang, Zhong, Huang, Meiyan, Liu, Shuang, Durrani, Tariq S., Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, 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, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martin, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, 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, Zhang, Junjie James, Series Editor, Liu, Xin, editor, Na, Zhenyu, editor, Wang, Wei, editor, Mu, Jiasong, editor, and Zhang, Baoju, editor

Published
2020
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9. Hidden Markov Model-Based Sense-Through-Foliage Target Detection Approach

Author

Zhao, Ganlin, Liang, Qilian, Durrani, Tariq S., Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, 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, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martin, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, 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, Zhang, Junjie James, Series Editor, Liu, Xin, editor, Na, Zhenyu, editor, Wang, Wei, editor, Mu, Jiasong, editor, and Zhang, Baoju, editor

Published
2020
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11. Image-Based Beam Tracking With Deep Learning for mmWave V2I Communication Systems

Author

Zhong, Weizhi, Zhang, Lulu, Jin, Haowen, Liu, Xin, Zhu, Qiuming, He, Yi, Ali, Farman, Lin, Zhipeng, Mao, Kai, and Durrani, Tariq S.

Abstract

Effective beam alignment is essential for vehicle-to-infrastructure (V2I) millimeter wave (mmWave) communication systems, particularly in high-mobility vehicle scenarios. This paper explores a three-dimensional (3D) vehicle environment and introduces a novel deep learning (DL)-based beam search method that incorporates an image-based coding (IBC) technique. The mmWave beam search is approached as an image processing problem based on situational awareness. We propose IBC to leverage the locations, sizes, and information of vehicles, and utilize convolutional neural network (CNN) to train the image dataset. Consequently, the optimal beam pair index(BPI)can be determined. Simulation results demonstrate that the proposed beam search method achieves satisfactory performance in terms of accuracy and robustness compared to conventional methods.

Published
2024
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12. Secure Rate Maximization for ISAC-UAV Assisted Communication Amidst Multiple Eavesdroppers

Author

Liu, Yuemin, Liu, Xin, Liu, Zechen, Yu, Yingfeng, Jia, Min, Na, Zhenyu, and Durrani, Tariq S

Abstract

Unmanned aerial vehicles (UAVs) equipped with integrated sensing and communication (ISAC) technology have been employed in the field of communication. In this paper, we propose an ISAC-UAV assisted secure communication system amidst multiple eavesdroppers. In each time slot, we implement ISAC and communication functions. Since there are multiple eavesdroppers in the system, jammer UAV is required to send jamming signals to the eavesdroppers. During the ISAC process, the source UAV identifies multiple eavesdroppers, relaying their position information to a jammer UAV. During the communication process, multiple eavesdroppers attempt to intercept the communication link between source UAV and users. We use the center of all users as the horizontal location of the jammer UAV. To maximize the secure data transmit rate, we propose a joint optimization problem involving user scheduling, transmit power, and source UAV trajectory. We break down the non-convex optimization problem into three subproblems, and then achieve the suboptimal solution to the original problem through iteratively optimizing these subproblems. Simulation results indicate that the proposed solution can achieve significant secure transmit rate even in the presence of multiple eavesdroppers.

Published
2024
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13. Evaluation Hand-Craft Features for Person Re-identification

Author

Zhang, Zhong, Huang, Meiyan, Liu, Shuang, Durrani, Tariq S., Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Ruediger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Mu, Jiasong, editor, Jia, Min, editor, Wang, Wei, editor, Feng, Xuhong, editor, and Zhang, Baoju, editor

Published
2019
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17. MIMO Identical Eigenmode Transmission System (IETS) - A Channel Decomposition Perspective

Author

Shakir, M. Zeeshan and Durrani, Tariq S.

Subjects
Computer Science - Information Theory, Computer Science - Networking and Internet Architecture
Abstract

In the past few years considerable attention has been given to the design of Multiple-Input Multiple-Output (MIMO) Eigenmode Transmission Systems (EMTS). This paper presents an in-depth analysis of a new MIMO eigenmode transmission strategy. The non-linear decomposition technique called Geometric Mean Decomposition (GMD) is employed for the formation of eigenmodes over MIMO flatfading channel. Exploiting GMD technique, identical, parallel and independent transmission pipes are created for data transmission at higher rate. The system based on such decomposition technique is referred to as MIMO Identical Eigenmode Transmission System (IETS). The comparative analysis of the MIMO transceiver design exploiting nonlinear and linear decomposition techniques for variable constellation is presented in this paper. The new transmission strategy is tested in combination with the Vertical Bell Labs Layered Space Time (V-BLAST) decoding scheme using different number of antennas on both sides of the communication link. The analysis is supported by various simulation results.

Published
2010

28. Optimal Trajectory and Resource Allocation for RSMA-UAV Assisted IoT Communications

Author

Feng, Jihan, Liu, Xin, Liu, Zechen, and Durrani, Tariq S.

Abstract

Unmaned aerial vehicle (UAV) can be deployed as an aerial base station (BS) of Internet of Things (IoT) due to its high mobility and low cost, while the ground BSs are absent or overload. We propose a rate splitting multiple access (RSMA)-UAV assisted IoT communication model, where the UAV flies over the target area and provide communication services for multiple ground users in pairs. In the RSMA-UAV scheme, the information of each ground user is split into common information and private information. In a user pair, the common information is decoded by all the users and the private information is only decoded by a specific user. The RSMA-UAV can control the inter-user interference by adjusting the split of common and private information, thus improving the rate of ground users. We formulate an optimization problem to maximize the system throughput by jointly optimizing communication schedule, common rate, transmit power and UAV flight trajectory. By leveraging block coordinate descent technique, we decompose the non-convex optimization problem into some solvable subproblems, and propose an alternating iterative optimization algorithm to achieve the suboptimal solutions. The simulations have shown that the RSMA-UAV scheme can achieve higher throughout than the orthogonal multiple access (OMA)-UAV scheme, and improve the minimum average achievable rate of users compared with the non-orthogonal multiple access (NOMA)-UAV scheme.

Published
2024
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29. Introduction

Author

Durrani, Tariq S., primary, Wang, Wei, additional, and Forbes, Sheila M, additional

Published
2018
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38. Intelligent Computing: The Latest Advances, Challenges, and Future

Author

Zhu, Shiqiang, primary, Yu, Ting, additional, Xu, Tao, additional, Chen, Hongyang, additional, Dustdar, Schahram, additional, Gigan, Sylvain, additional, Gunduz, Deniz, additional, Hossain, Ekram, additional, Jin, Yaochu, additional, Lin, Feng, additional, Liu, Bo, additional, Wan, Zhiguo, additional, Zhang, Ji, additional, Zhao, Zhifeng, additional, Zhu, Wentao, additional, Chen, Zuoning, additional, Durrani, Tariq S., additional, Wang, Huaimin, additional, Wu, Jiangxing, additional, Zhang, Tongyi, additional, and Pan, Yunhe, additional

Published
2023
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42. Nonlinear Adaptive Speech Enhancement Inspired by Early Auditory Processing

Author

Hussain, Amir, Durrani, Tariq S., Alkulaibi, Ali, Mtetwa, Nhamo, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Chollet, Gérard, editor, Esposito, Anna, editor, Faundez-Zanuy, Marcos, editor, and Marinaro, Maria, editor

Published
2005
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