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13th International Conference on Intelligent Control and Information processing, ICICIP 2025

作者： Li, Jiahao Wang, Zhongshuai Ghazali, Kamarul Hawari Bin Yan, Suqing Lan, Rushi Sun, Xiyan Luo, Xiaonan Guangxi Key Lab. of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin541004 China Centre for Advanced Industrial Technology University of Malaysia Pahang Al-Sultan Abdullah Pahang Pekan26600 Malaysia Int. Joint Research Lab. of Spatio-temporal Information and Intelligent Location Services Guilin University of Electronic Technology Guilin541004 China

ISBN: (纸本)9798331516147

Privacy-preserving image generation is particularly crucial in fields like healthcare, where data are both sensitive and limited. However, effective privacy preservation often compromises the visual quality and utility of the generated images due to privacy budget constraints. To address this issue, in this paper, We propose a novel network architecture, IRSEnet, which combines multi-scale feature extraction technology and residual channel attention mechanisms, aiming to enhance the visual quality of generated images and improve the performance of downstream classification tasks under differential privacy. The differential privacy mechanism ensures the security of sensitive data during training, while the multi-scale feature extraction module enhances feature extraction capabilities through parallel convolutional layers at multiple scales. Additionally, the channel attention module dynamically adjusts channel weights to focus on the most discriminative features. Experimental results demonstrate that this model significantly improves the utility of generated images and the accuracy of downstream classification tasks while preserving privacy. Future work will explore the application of this approach on larger datasets and across more diverse tasks. © 2025 IEEE.

关键词： Differential privacy

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IRSEnet: Differentially Private image Generation with Multi-Scale Feature Extraction and Residual Channel Attention

IRSEnet: Differentially Private Image Generation with Multi-...

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International Conference on Intelligent Control and Information processing (ICICIP)

作者： Jiahao Li Zhongshuai Wang Kamarul Hawari Bin Ghazali Suqing Yan Rushi Lan Xiyan Sun Xiaonan Luo Guangxi Key Lab. of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin China Centre for Advanced Industrial Technology University of Malaysia Pahang Al-Sultan Abdullah Pekan Pahang Malaysia Int. Joint Research Lab. of Spatio-temporal Information and Intelligent Location Services Guilin University of Electronic Technology Guilin China

ISBN: (数字)9798331516147

ISBN: (纸本)9798331516154

关键词： Training Differential privacy Privacy Visualization Accuracy image synthesis Computational modeling Feature extraction Security Synthetic data

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Improvement and Realization of DSR Routing Protocol with QoS Support in Wireless Mesh Networks

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China communications 2009年第1期6卷 123-127页

作者： Gu Xiaoyan , Liu Feng image processing and image communications key lab. Nanjing University of Posts and Telecommunications, Nanjing 210003, China Image Processing and Image Communications Key Lab Nanjing University of Posts and Telecommunications Nanjing 210003 China

In Wireless Mesh Network,multimedia applications require the network to guarantee Quality-of-Service(QoS). A new QoS-aware routing protocol based on DSR named QDSR(QoS-DSR) is further proposed. QDSR guarantees the QoS of application, such as bandwidth and delay, defines routing cost function according to the number of hops of path and buffer and chooses the best path based on routing cost. Simulation results show that, compared with DSR, QDSR greatly improves the throughput, reduces the average end to end delay, improves the efficiency, satisfies the QoS of application better and has stronger applicability and expansibility.

关键词： Wireless Mesh network Quality-of-Service routing protocol bandwidth delay routing cost function

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An efficient fast inter mode decision algorithm for h.264/avc ***

An efficient fast inter mode decision algorithm for h.264/av...

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2009 WRI International Conference on communications and Mobile Computing, CMC 2009

作者： Huang, Huaibin Hu, Dong Key Lab. of Image Processing and Image Communications of Jiangsu Province Nanjing University of Posts and Telecom Nanjing 210003 China

ISBN: (纸本)9780769535012

An efficient fast inter mode decision algorithm for the baseline H.264/AVC video coding is proposed in this paper. The main idea of the algorithm is to reduce the number of candidate modes for Rate Distortion Optimization(RDO) by using early mode detection in four different levels, viz. SKIP mode detection, type detection at macroblock-level, type detection at submacroblock-level and intra modes detection. In addition, the correlation of cost of current MB and the one of previous frame, as well as the cost's monotonous property are both used to help the mode decision. Compared to JM8.6 reference software, our algorithm can save encoding time 71.743% on average with negligible PSNR loss, which is very helpful for H.264/AVC inter frame encoding. © 2009 IEEE.

关键词： Electric distortion

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Partical swarm optimization based unequal loss protection of embedded video streams

Partical swarm optimization based unequal loss protection of...

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2010 IEEE 12th International Conference on Communication Technology, ICCT'2010

作者： Hu, Jiajing Hu, Dong Key Lab. of Image Processing and Image Communications of Jiangsu Province Nanjing University of Posts and Telecom Nanjing 210003 China

ISBN: (纸本)9781424468690

This paper presents a new scheme for optimal packetization of scalab.e multimedia data over lossy network. By assigning an unequal amount of forward error correction (FEC) bits to each segment of transmission packets, the proposed algorithm protects a progressive bitstream generated by a three-dimensional set partitioning in hierarchical trees (3-D SPIHT) algorithm. The partical swarm optimization (PSO) algorithm is used to reasonably allocate bits between source coding and channel coding across packets. Experimental results show that the proposed algorithm provides close to optimal average peak signal-to-noise ratio performance and that its'running time is significantly lower than that of previously known solution. © 2010 IEEE.

关键词： Signal to noise ratio

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Symbolic dynamics analysis of pathological signals

Symbolic dynamics analysis of pathological signals

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2011 1st International Workshop on Complexity and Data Mining, IWCDM 2011

作者： Wang, Jun Wu, Jun Image Processing and Image Communications Key Lab. School of Geography and Biological Information Nanjing Univ. of Posts and Telecomm Nanjing 210003 China

ISBN: (纸本)9781457720079

Paper uses symbolic dynamics to study heartbeat time series from the normal subjects, patients with congestive heart failure and cardiac arrest patients. The results show that entropy value of normal people's heart beat signals is the maximum. Information entropy value of congestive heart failure patient is decreasing. Cardiac arrest patients' information entropy is the smallest. It is corresponding that patients have entered into dangerous stage in clinical. Clinical treatment of patients at this time is a critical period. The results are of great significance on the clinical automatically diagnosis. It can play a role in timely warning especially in the long ambulatory ECG monitoring to save the patient's life. © 2011 IEEE.

关键词： Diagnosis

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Robust license plate detection through auxiliary information and context fusion model 2nd

Robust license plate detection through auxiliary information...

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2nd Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2019

作者： Wang, Ning Liu, Feng Gan, Zongliang Jiangsu Province Key Lab on Image Processing and Image Communications Nanjing University of Posts and Telecommunications Nanjing210003 China

ISBN: (纸本)9783030317256

License plate detection has wide applications in the intelligent transportation system, while it still remains challenges to improve the robustness under various shooting distance and observation angles. To get better performance, a novel convolutional-neural-network-based method is proposed, which is achieved with auxiliary information and context fusion model. First, the auxiliary information is employed in our framework, which corresponds with resolutions, orientations and shapes of license plates. Specifically, the multiple resolutions are collected through integrating multi-level features of convolution hierarchy. Besides the various scales and ratios, the region proposal network RPN with multi-angle anchors and branching structure is applied to generate proper proposals. Second, an effective context fusion model is designed to fully exploit the hidden correlation between license plates and contextual properties. The local and contextual features are independently learned in the dual pathways, which are later joint to form a powerful representation in subsequent layers. Comprehensive experiments on the publicly availab.e datasets confirm the effectiveness of the proposed method. © Springer Nature Switzerland AG 2019.

关键词： Convolution

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A new super-resolution reconstruction method combining narrow quantization constraint set and motion estimation for H.264 compressed video

A new super-resolution reconstruction method combining narro...

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International Conference on image and Graphics

作者： Hu, Dong Zhao, Yingxue Xiao, Peng Jiangsu Provincial Key Lab of Image Processing and Image Communications Nanjing University of Posts and Telecommunications Nanjing 210003 China

ISBN: (纸本)9780769545417

Super-resolution (SR) reconstruction technique is mainly a task of reconstructing high resolution images from a sequence of low resolution images. The super-resolution technique for H.264 compressed video has been focused by many researchers recently. This paper briefly analyzes the narrow quantization constraint set method (NQCS), and then, in consideration of motion characteristic information of H.264 compressed video, proposes a new SR reconstruction method which combines NQCS with motion characteristic information, which are spatial domain motion estimation and frequency domain motion noise respectively. Experimental results of different standard test sequences compressed by H.264 are given. The simulation shows that both the NQCS+Mnoise method which combines NQCS with frequency domain motion noise, and the NQCS+M method which combines NQCS with spatial domain motion estimation, can get higher PNSR value than NQCS. Moreover, the NQCS+M method has better performance than NQCS+Mnoise method, and our proposed method is suitable for the SR reconstruction of H.264 compressed video. © 2011 IEEE.

关键词： Motion estimation

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Unequal loss protection of embedded streams combining particle swarm optimization and local search

Unequal loss protection of embedded streams combining partic...

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International Conference on Multimedia and Signal processing

作者： Hu, Jiajing Hu, Dong Key Lab of Image Processing and Image Communications of Jiangsu Province Nanjing University of Posts and Telecom Nanjing 210003 China

ISBN: (纸本)9780769543567

FEC-based multiple description coding (MDC) is an effective method for the transmission of scalab.e video stream over noisy network. However, given the transmission bandwith, it's time-consuming to find the optimal packet number and packet length as well as reasonably allocate bits between source coding and channel coding across the packets. In this paper, we state the optimal unequal error protection(UEP) as a two-level optimization problem and use a rate-optimal solution in initial step of searching. Then, we propose a new scheme, which combines the particle swarm optimization (PSO) with the local search(LS) algorithms, so that optimal solution can be found in more efficient way. Experimental results for the 3D set partitioning in hierarchical trees (SPIHT) coders show that the new algorithm provides close to optimal average peak signal-to-noise ratio performance and that its' running time is obviously lower than that of previously known algorithms.© 2011 IEEE.

关键词： Particle swarm optimization (PSO)

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Liver Tumor Segmentation Based on Three-Channel Cascaded SEU-Nets and C-LSTM 13

Liver Tumor Segmentation Based on Three-Channel Cascaded SEU...

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13th International Conference on Wireless communications and Signal processing, WCSP 2021

作者： Li, Yarong Hu, Dong Nanjing University of Posts and Telecommunications Jiangsu Province's Key Lab of Image Processing and Image Communications Nanjing China

ISBN: (纸本)9781665407854

An abdominal CT liver tumor segmentation algorithm based on three-channel cascade SEU-Nets and C-LSTM is proposed in this paper. Concerning the accuracy of most known algorithms is limited by using single-phase CT images, the proposed method takes advantage of the different characteristics of the lesion area in the venous phase, arterial phase and delayed phase, and the correlation between slices in enhanced CT images. It uses three-channel SEU-Nets as the encoder to extract image features of slices in three phases, and uses 3D convolution to extract the relationship between slices for the same location at different phases. And then it uses C-LSTM to extract the inter-slice sequence feature relationship. Finally, the decoder outputs fine segmentation of liver tumor output. 40 sets of high-quality abdominal-enhanced CT images of the liver and liver tumors used in the experiment were collected in the provincial central hospital and annotated by experts. Comparisons are carried out with well-known methods, such as improved CFCNs, H-DenseUNet network and DBAs-based multi-scale DC-CUNets segmentation network. Experimental results show that the average segmentation accuracy of proposed algorithm is 7.04% higher than that of the multi-scale DC-CUNets segmentation network based on DBAs, and the DICE coefficient is improved by 4.89%. © 2021 IEEE.

关键词： Long short-term memory

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