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学者姓名：宋志刚
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医学影像共享是医疗信息云共享中最重要的部分，因为医疗信息80%以上是医学影像，但信息共享面临数据安全、隐私保护和信息检索等问题。虽然已有很多密文域可逆信息隐藏(RDH-EI, Reversible Data Hiding in Encrypted Image)方案，但一般不能直接应用于DICOM医学影像上。为了满足云服务中DICOM文件的隐私保护和信息检索需求，文章提出一种基于ZUC加性同态和多层差值直方图平移的DICOM图像RDH-EI方案。所提方案不改变DICOM文件格式，不增加文件大小，且图像解密和信息提取可分离。实验结果表明，所提出的方案具有良好的灵活性和计算效率，是一种适用云共享的RDH-EI方案。
Keyword ：
DICOM DICOM ZUC算法 ZUC算法 加性同态 加性同态 可逆信息隐藏 可逆信息隐藏 多层差值直方图平移 多层差值直方图平移
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| GB/T 7714 | 郑梓劲 , 宋志刚 , 杨文琴 et al. 基于国密加性同态的医学影像可逆信息隐藏方法 [J]. | 长江信息通信 , 2024 , 37 (03) : 1-6 . |
| MLA | 郑梓劲 et al. "基于国密加性同态的医学影像可逆信息隐藏方法" . | 长江信息通信 37 . 03 (2024) : 1-6 . |
| APA | 郑梓劲 , 宋志刚 , 杨文琴 , 李代松 , 郑绍华 . 基于国密加性同态的医学影像可逆信息隐藏方法 . | 长江信息通信 , 2024 , 37 (03) , 1-6 . |
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It has been widely known that long non-coding RNA (lncRNA) plays an important role in gene expression and regulation. However, due to a few characteristics of lncRNA (e.g., huge amounts of data, high dimension, lack of noted samples, etc.), identifying key lncRNA closely related to specific disease is nearly impossible. In this paper, the authors propose a computational method to predict key lncRNA closely related to its corresponding disease. The proposed solution implements a BPSO based intelligent algorithm to select possible optimal lncRNA subset, and then uses ML-ELM based deep learning model to evaluate each lncRNA subset. After that, wrapper feature extraction method is used to select lncRNAs, which are closely related to the pathophysiology of disease from massive data. Experimentation on three typical open datasets proves the feasibility and efficiency of our proposed solution. This proposed solution achieves above 93% accuracy, the best ever.
Keyword ：
Binary Particle Swarm Optimization Binary Particle Swarm Optimization Expression Profile Expression Profile Extreme Learning Machine Extreme Learning Machine Long Non-Coding RNA Long Non-Coding RNA
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| GB/T 7714 | Yang, Wenqing , Zheng, Xianghan , Huang, QiongXia et al. Combining BPSO and ELM Models for Inferring Novel lncRNA- Disease Associations [J]. | INTERNATIONAL JOURNAL OF DATA WAREHOUSING AND MINING , 2023 , 19 (2) . |
| MLA | Yang, Wenqing et al. "Combining BPSO and ELM Models for Inferring Novel lncRNA- Disease Associations" . | INTERNATIONAL JOURNAL OF DATA WAREHOUSING AND MINING 19 . 2 (2023) . |
| APA | Yang, Wenqing , Zheng, Xianghan , Huang, QiongXia , Liu, Yu , Chen, Yimi , Song, ZhiGang . Combining BPSO and ELM Models for Inferring Novel lncRNA- Disease Associations . | INTERNATIONAL JOURNAL OF DATA WAREHOUSING AND MINING , 2023 , 19 (2) . |
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The unsupervised domain-adaptive vehicle re-identification approach aims to transfer knowledge from a labeled source domain to an unlabeled target domain; however, there are knowledge differences between the target domain and the source domain. To mitigate domain discrepancies, existing unsupervised domain-adaptive re-identification methods typically require access to source domain data to assist in retraining the target domain model. However, for security reasons, such as data privacy, data exchange between different domains is often infeasible in many scenarios. To this end, this paper proposes an unsupervised domain-adaptive vehicle re-identification method based on source-free knowledge transfer. First, by constructing a source-free domain knowledge migration module, the target domain is consistent with the source domain model output to train a generator to generate the "source-like samples". Then, it can effectively reduce the model knowledge difference and improve the model's generalization performance. In the experiment, two mainstream public datasets in this field, VeRi776 and VehicleID, are tested experimentally, and the obtained rank-k (the cumulative matching features) and mAP (the mean Average Precision) indicators are both improved, which are suitable for object re-identification tasks when data between domains cannot be interoperated.
Keyword ：
joint training joint training pseudo label pseudo label source-free knowledge transfer source-free knowledge transfer unsupervised domain adaptation unsupervised domain adaptation vehicle re-identification vehicle re-identification
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| GB/T 7714 | Song, Zhigang , Li, Daisong , Chen, Zhongyou et al. Unsupervised Vehicle Re-Identification Method Based on Source-Free Knowledge Transfer [J]. | APPLIED SCIENCES-BASEL , 2023 , 13 (19) . |
| MLA | Song, Zhigang et al. "Unsupervised Vehicle Re-Identification Method Based on Source-Free Knowledge Transfer" . | APPLIED SCIENCES-BASEL 13 . 19 (2023) . |
| APA | Song, Zhigang , Li, Daisong , Chen, Zhongyou , Yang, Wenqin . Unsupervised Vehicle Re-Identification Method Based on Source-Free Knowledge Transfer . | APPLIED SCIENCES-BASEL , 2023 , 13 (19) . |
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鉴于平扫CT中血管未增强、肺动静脉区分难度加大而造成的标注成本高、样本少等特点，提出一种基于双任务一致性正则的半监督肺动静脉分离方法。首先以半监督框架为基础模型，引入回归真实标签的符号距离图作为辅助任务，以增强网络对动静脉几何形状特征的学习。然后，为了平衡不同任务之间的关系，在网络中嵌入多任务联合损失函数，以提高整个模型的性能。经实验验证，所提出的方法动静脉分离结果要优于V-Net、3D U-Net等方法。为了进一步验证方法的有效性，对网络进行了数据集划分实验。实验结果显示，随着标注数据量和未标注数据量的增加，所提方法具有进一步提高性能的潜力。
Keyword ：
半监督 半监督 多任务 多任务 平扫CT 平扫CT 肺动静脉分离 肺动静脉分离 距离图 距离图
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| GB/T 7714 | 杨文琴 , 李招培 , 宋志刚 . 基于双任务一致性正则的肺动静脉分离方法 [J]. | 信息技术与信息化 , 2023 , 5 (11) : 208-212 . |
| MLA | 杨文琴 et al. "基于双任务一致性正则的肺动静脉分离方法" . | 信息技术与信息化 5 . 11 (2023) : 208-212 . |
| APA | 杨文琴 , 李招培 , 宋志刚 . 基于双任务一致性正则的肺动静脉分离方法 . | 信息技术与信息化 , 2023 , 5 (11) , 208-212 . |
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目前无监督行人再识别是直接利用全局特征计算相似性，这会导致伪标签生成质量不佳，并且基于卷积神经网络的方法可能会产生细节丢失。针对这些问题，本文设计了一种基于局部特征融合的无监督行人再识别网络，通过随机滑窗的图像编码方式来解决信息丢失问题。为了产生可靠的伪标签，通过Vision Transformer独有的“抛弃特征”作为局部变量来计算局部相似性，并且融合摄像头相似性以提高总体样本相似性计算的准确性，提升伪标签生成的质量。实验结果表明，该方法在公开数据集Market-1501和DukeMTMC-reID上可以大幅提升模型性能。
Keyword ：
无监督学习 无监督学习 聚类算法 聚类算法 行人再识别 行人再识别 视觉Transformer 视觉Transformer
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| GB/T 7714 | 杨文琴 , 丁肇丰 , 宋志刚 . ViT融合局部特征的无监督行人再识别研究 [J]. | 福建电脑 , 2023 , 39 (12) : 8-14 . |
| MLA | 杨文琴 et al. "ViT融合局部特征的无监督行人再识别研究" . | 福建电脑 39 . 12 (2023) : 8-14 . |
| APA | 杨文琴 , 丁肇丰 , 宋志刚 . ViT融合局部特征的无监督行人再识别研究 . | 福建电脑 , 2023 , 39 (12) , 8-14 . |
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With the development of information technology, machine translation technologies play a crucial role in cross-language communication. However, there is a problem of information loss in machine translation. In view of the common problem, this paper proposes three Transform-Information Combination (Transformer-IC) models based on information combination method. The models are based on the Transformer and select different middle-layer information to compensate the output through arithmetic mean combination method, linear transformation method and multi-layer information combination method respectively. Experimental results based on Linguistic Data Consortium (LDC) Chinese-to-English corpus and International Workshop on Spoken Language Translation (IWSLT) English-to-German corpus show that the BLEU values of all kinds of Transformer-IC model are higher than that of the reference model, in particular the arithmetic mean combination method improves the BLEU value by 1.9. Compared with the Bert model, the results show that even though the Bert model has a good performance, the Transformer-IC models are better than the Bert model. Transformer-IC models can make full use of the middle-layer information and effectively avoid the problem of information loss. © 2021 IEEE
Keyword ：
Computational linguistics Computational linguistics Computer aided language translation Computer aided language translation Integrated circuits Integrated circuits Linear transformations Linear transformations Mathematical transformations Mathematical transformations
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| GB/T 7714 | Song, Zhigang , Chai, Jiazhao , Shang, Wenqian et al. Transformer-ic: The solution to information loss [C] . 2021 : 97-101 . |
| MLA | Song, Zhigang et al. "Transformer-ic: The solution to information loss" . (2021) : 97-101 . |
| APA | Song, Zhigang , Chai, Jiazhao , Shang, Wenqian , Yuning, Guo . Transformer-ic: The solution to information loss . (2021) : 97-101 . |
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Traditional centralized digital copyright protection is weak in security and difficult to manage. In order to protect digital assets from unauthorized use and to solve the centralized regulatory challenges, blockchain technology is used to enhance the protection of digital works copyrights. This paper proposed a digital works copyright protection architecture based on the Consortium Blockchain, and elaborate on the security problems and solutions faced by the architecture. Moreover, the Diffie-Hellman algorithm is improved based on the Shamir algorithm to make it more suitable for the characteristics of blockchain. Finally, a smart contract is written according to the characteristics and process of digital copyright protection, and a Fabric-based digital copyright protection solution is implemented. The feasibility and effectiveness of using blockchain for digital copyright protection proposed in this paper are proved through experiments, Furthermore, the extensibility of the solution is discussed. © 2021, Springer Nature Singapore Pte Ltd.
Keyword ：
Blockchain Blockchain Copyrights Copyrights
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| GB/T 7714 | Song, Zhigang , Yu, Zaifu , Shang, Wenqian et al. A Digital Copyright Protection Method Based on Blockchain [C] . 2021 : 486-498 . |
| MLA | Song, Zhigang et al. "A Digital Copyright Protection Method Based on Blockchain" . (2021) : 486-498 . |
| APA | Song, Zhigang , Yu, Zaifu , Shang, Wenqian , Li, YaXuan . A Digital Copyright Protection Method Based on Blockchain . (2021) : 486-498 . |
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This paper mainly studies the dynamic identification of hot topics and their trend prediction: the identification methods of hot topics are studied from the two dimensions of content and form; the trend prediction method is completed from the two dimensions of media attention and emotional tendency. This paper develops a hot topic recognition method based on formal feature ranking. This paper compares the advantages and disadvantages of traditional methods, and proposes a high-frequency co-occurrence clustering strategy based on minimum similarity, which effectively solves the timeliness requirements of real-time dynamic hot spot recognition. Based on the recognition of hot topics, this article will jointly complete the trend prediction of hot topics from the changes in media attention and emotional orientation. We have encapsulated the hot topic recognition method based on high-frequency co-occurrence into a module and applied it in the national language and writing public opinion monitoring system. © 2021 IEEE.
Keyword ：
Forecasting Forecasting Social aspects Social aspects
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| GB/T 7714 | Song, Zhigang , Song, Kang , Cheng, Nanchang et al. Research on Internet Public Opinion Recognition Method Based on High Frequency Co-occurrence [C] . 2021 : 237-242 . |
| MLA | Song, Zhigang et al. "Research on Internet Public Opinion Recognition Method Based on High Frequency Co-occurrence" . (2021) : 237-242 . |
| APA | Song, Zhigang , Song, Kang , Cheng, Nanchang , Li, Jiao , Shang, Wenqian , Zou, Yu . Research on Internet Public Opinion Recognition Method Based on High Frequency Co-occurrence . (2021) : 237-242 . |
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Person re-identification (re-ID) is the task of matching the same individuals across multiple cameras, and its performance is greatly influenced by background clutter. Most re-ID methods remove background clutter using hard manners, such as the use of segmentation algorithms. However, the hard manner may damage the structure information and smoothness of original images. In this work, we propose a unidirectional information-interaction network ((UIN)-N-2) that consists of a global stream (G-Stream) and a background-graying stream (BGg-Stream). The G-Stream and BGg-Stream carry out unidirectional information interaction such that their features are complementary. We further propose a soft manner with the (UIN)-N-2 to weaken background clutter by background-graying. The soft manner can help the (UIN)-N-2 filter out background interference and retain some informative background cues. Extensive evaluations demonstrate that our method significantly outperforms many state-of-the-art approaches in the challenging Market-1501, DukeMTMC-reID, and CUHK03-NP datasets. (C) 2021 SPIE and IS&T
Keyword ：
background-grey background-grey person re-identification person re-identification unidirectional information interaction unidirectional information interaction
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| GB/T 7714 | Yang, Qingqing , Wu, Junyi , Song, Qishan et al. Unidirectional information-interaction network for person re-identification [J]. | JOURNAL OF ELECTRONIC IMAGING , 2021 , 30 (4) . |
| MLA | Yang, Qingqing et al. "Unidirectional information-interaction network for person re-identification" . | JOURNAL OF ELECTRONIC IMAGING 30 . 4 (2021) . |
| APA | Yang, Qingqing , Wu, Junyi , Song, Qishan , Gao, Zhipeng , Huang, Liqin , Song, Zhigang . Unidirectional information-interaction network for person re-identification . | JOURNAL OF ELECTRONIC IMAGING , 2021 , 30 (4) . |
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针对现有中文微博观点分类方法对上下文利用不足、数据表示稀疏和特征依赖于人工设计等问题,提出基于卷积神经网络的中文微博观点分类方法.首先利用交互上下文扩充不同主题下的微博内容,使用低维密集向量初始化微博文本.然后构造卷积神经网络模型,实现特征抽取和组合.最后基于softmax分类函数估计中文微博观点类别.实验表明,相比基准方法,文中方法在精确度和F1值上的效果更好.
Keyword ：
中文微博 中文微博 卷积神经网络 卷积神经网络 观点分类 观点分类
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| GB/T 7714 | 廖祥文 , 张丽瑶 , 宋志刚 et al. 基于卷积神经网络的中文微博观点分类 [J]. | 模式识别与人工智能 , 2016 , 29 (12) : 1075-1082 . |
| MLA | 廖祥文 et al. "基于卷积神经网络的中文微博观点分类" . | 模式识别与人工智能 29 . 12 (2016) : 1075-1082 . |
| APA | 廖祥文 , 张丽瑶 , 宋志刚 , 程学旗 , 陈国龙 . 基于卷积神经网络的中文微博观点分类 . | 模式识别与人工智能 , 2016 , 29 (12) , 1075-1082 . |
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