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Intellicise communication system: model-driven semantic communications
Zhang Ping, Xu Xiaodong, Dong Chen, Han Shujun, Wang Bizhu
The Journal of China Universities of Posts and Telecommunications    2022, 29 (1): 2-12.   DOI: 10.19682/j.cnki.1005-8885.2022.2002
Abstract891)            Save
As one of the critical technologies for the 6th generation mobile communication system (6G) mobile communication systems, artificial intelligence (AI) technology will provide complete automation for connecting the virtual and physical worlds. In order to construct the future ubiquitous intelligent network, people are beginning to rethink how mobile communication systems transmit and exploit intelligent information. This paper proposes a new communication paradigm, called the Intellicise communication system: model-driven semantic communication. Intellicise communication system is built on top of the traditional communication system and innovatively adds a new feature dimension on top of the traditional source coding, which enables the communication system to evolve from the traditional transmission of bit to the transmission of  model . Like the semantic base (Seb) for semantic communication, the model is considered as the new feature obtained from the joint source-channel coding. The sink node can re-construct the original signal based on the received model and the encoded sequence. In addition, the performance evaluation metrics and the implementation details of the Intellicise communication system are discussed in this paper. Finally, preliminary results of model-driven image transmission in the Intellicise communication system are presented.
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Research on cross-chain and interoperability for blockchain system

李鸣 邱鸿霖 徐泉清 宋文鹏 Liu Baixiang
The Journal of China Universities of Posts and Telecommunications    2021, 28 (5): 1-17.   DOI: 10. 19682/ j. cnki. 1005-8885. 2021. 0029
Abstract376)            Save

At present, there is an urgent need for blockchain interoperability technology to realize interconnection between various blockchains, data communication and value transfer between blockchains, so as to break the ‘ value silo’ phenomenon of each blockchain. Firstly, it lists what people understand about the concept of interoperability. Secondly, it gives the key technical issues of cross-chain, including cross-chain mechanism, interoperability, eventual consistency, and universality. Then, the implementation of each cross-chain key technology is analyzed, including Hash-locking, two-way peg, notary schemes, relay chain scheme, cross-chain protocol, and global identity system. Immediately after that, five typical cross-chain systems are introduced and comparative analysis is made. In addition, two examples of cross-chain programmability and their analysis are given. Finally, the current state of cross-chain technology is summarized from two aspects: key technology implementation and cross-chain application enforcement. The cross-chain technology as a whole has formed a centralized fixed mechanism, as well as a trend of modular design, and some of the solutions to mature applications were established in the relevant standards organizations, and the cross-chain technology architecture tends to be unified, which is expected to accelerate the evolution of the open cross-chain network that supports the real needs of the interconnection of all chains.



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Native intelligence for 6G mobile network: technical challenges, architecture and key features
Liu Guangyi, Deng Juan, Zheng Qingbi, Li Gang, Sun Xin, Huang Yuhong
The Journal of China Universities of Posts and Telecommunications    2022, 29 (1): 27-40.   DOI: 10.19682/j.cnki.1005-8885.2022.2004
Abstract335)            Save
The application of the artificial intelligence (AI) technology in the 5th generation mobile communication system (5G) networks promotes the development of the mobile communication network and its application in vertical industries, however, the application models of "patching" and "plug-in" have hindered the effect of AI applications. Meanwhile, the application of AI in all walks of life puts forward requirements for new capabilities of the future network, such as distributed training, real-time collaborative inference, local data processing, etc. , which require "native intelligence design” in future networks. This paper discusses the requirements of native intelligence in the 6th generation mobile communication system (6G) networks from the perspectives of 5G intelligent network challenges and the  ubiquitous intelligence  vision of 6G, and analyzes the technical challenges of the AI workflows in its lifecycle and the AI as a service (AIaaS) in cloud network. The progress and deficiencies of the current research on AI functional architecture in various industry organizations are summarized. The end-to-end functional architecture for native AI for 6G network and its three key technical characteristics are proposed: quality of AI services (QoAIS) based AI service orchestration for its full lifecycle, deep integration of native AI computing and communication, and integration of native AI and digital twin network. The directions of future research are also prospected.
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Modulation classification based on the collaboration of dual-channel CNN-LSTM and residual network
Li Hui, Li Shanshan, Zou Borong, Chen Yannan
The Journal of China Universities of Posts and Telecommunications    2022, 29 (1): 113-124.   DOI: 10.19682/j.cnki.1005-8885.2022.2012
Abstract318)            Save
Deep learning has recently been progressively introduced into the field of modulation classification due to its wide application in image, vision, and other areas. Modulation classification is not only the priority of cognitive radio and spectrum sensing, but also the link during signal demodulation. Combining the advantages of convolutional neural network (CNN), long short-term memory (LSTM), and residual network (ResNet), a modulation classification method based on dual-channel CNN-LSTM and ResNet is proposed to automatically classify the modulation signal more accurately. Specifically, CNN and LSTM are initially used to form a dual-channel structure to effectively explore the spatial and temporal features of the original complex signal. It solves the problem of only focusing on temporal or spatial aspects, and increases the diversity of features. Secondly, the features extracted from CNN and LSTM are fused, making the extracted features richer and conducive to signal classification. In addition, a convolutional layer is added within the residual unit to deepen the network depth. As a result, more representative features are extracted, improving the classification performance. Finally, simulation results on the radio machine learning (RadioML) 2018.01A dataset signify that the network's classification performance is superior to many classifiers in the literature.
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Shared experiences across multiple devices: a new digital interactive experience method for cultural heritage based on mixed reality
Lu Zhichao, Zhao Haiying
The Journal of China Universities of Posts and Telecommunications    2022, 29 (2): 1-12.   DOI: 10. 19682/ j. cnki. 1005-8885. 2022. 0011
Abstract308)      PDF       Save

In order to study the role of the new technological concept of shared experiences in the digital interactive experience of cultural heritage and apply it to the digital interactive experience of cultural heritage to solve the current problems in this field, starting from the mixed reality (MR) technology that the shared experiences rely on, proper software and hardware platforms were investigated and selected, a universal shared experiences solution was designed, and an experimental project based on the proposed solution was made to verify its feasibility. In the end, a proven and workable shared experiences solution was obtained. This solution included a proposed MR spatial alignment method, and it integrated the existing MR content production process and standard network synchronization functions. Furthermore, it is concluded that the introduction and reasonable use of new technologies can help the development of the digital interactive experience of cultural heritage. The shared experiences solution for the digital interactive experience of cultural heritage balances investment issues in the exhibition, display effect, and user experience. It can speed up the promotion of cultural heritage and bring the vitality of MR technology to relevant projects.

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Aerial edge computing for 6G
Mao Sun, Zhang Yan
The Journal of China Universities of Posts and Telecommunications    2022, 29 (1): 50-63.   DOI: 10.19682/j.cnki.1005-8885.2022.2006
Abstract304)            Save
In the 6th generation mobile communication system (6G) era, a large number of delay-sensitive and computation-intensive applications impose great pressure on resource-constrained Internet of things (IoT) devices. Aerial edge computing is envisioned as a promising and cost-effective solution, especially in hostile environments without terrestrial infrastructures. Therefore, this paper focuses on integrating aerial edge computing into 6G for providing ubiquitous computing services for IoT devices. This paper first presents the layered network architecture of aerial edge computing for 6G. The benefits, potential applications, and design challenges are also discussed in detail. Next, several key techniques like unmanned aerial vehicle (UAV) deployment, operation mode, offloading mode, caching policy, and resource management are highlighted to present how to integrated aerial edge computing into 6G. Then, the joint UAV deployment optimization and computation offloading method is designed to minimize the computing delay for a typical aerial edge computing network. Numerical results reveal the significant delay reduction of the proposed method compared with the other benchmark methods. Finally, several open issues for aerial edge computing in 6G are elaborated to provide some guidance for future research.
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Air interface design for edge intelligence
Zhang Zezhong, Chen Mingzhe, Xu Jie, Cui Shuguang
The Journal of China Universities of Posts and Telecommunications    2022, 29 (1): 13-26.   DOI: 10.19682/j.cnki.1005-8885.2022.2003
Abstract283)            Save
Recent breakthroughs in artificial intelligence (AI) give rise to a plethora of intelligent applications and services based on machine learning algorithms such as deep neural networks (DNNs). With the proliferation of Internet of things (IoT) and mobile edge computing, these applications are being pushed to the network edge, thus enabling a new paradigm termed as edge intelligence. This provokes the demand for decentralized implementation of learning algorithms over edge networks to distill the intelligence from distributed data, and also calls for new communication-efficient designs in air interfaces to improve the privacy by avoiding raw data exchange. This paper provides a comprehensive overview on edge intelligence, by particularly focusing on two paradigms named edge learning and edge inference, as well as the corresponding communication-efficient solutions for their implementations in wireless systems. Several insightful theoretical results and design guidelines are also provided.
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Semantic information processing in industrial networks
Yao Shengshi, Wang Sixian, Dai Jincheng, Niu Kai, Xu Wenjun, Zhang Ping
The Journal of China Universities of Posts and Telecommunications    2022, 29 (1): 41-49.   DOI: 10.19682/j.cnki.1005-8885.2022.2005
Abstract278)            Save
The industrial Internet of things (industrial IoT, IIoT) aims at connecting everything, which poses severe challenges to existing wireless communication. To handle the demand for massive access in future industrial networks, semantic information processing is integrated into communication systems so as to improve the effectiveness and efficiency of data transmission. The semantic paradigm is particularly suitable for the purpose-oriented information exchanging scheme in industrial networks. To illustrate its applicability, typical industrial data are investigated, i. e. , time series and images. Simulation results demonstrate the superiority of semantic information processing, which achieves a better rate-utility tradeoff than conventional signal processing.
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Augmented reality-based BIM multi-user collaboration system
Sun Heng, Qiao Xiuquan
The Journal of China Universities of Posts and Telecommunications    2022, 29 (1): 71-80.   DOI: 10.19682/j.cnki.1005-8885.2022.2008
Abstract261)            Save
The rapid development of building information modelling (BIM) and its enabling technologies has attracted extensive attention in the field of architecture, engineering and construction (AEC). By combining BIM models with the real world, the potential of BIM can be further exploited with the help of augmented reality (AR) technology. However, a BIM model usually involves a huge amount of data. Considering the limited computing capability of current mobile devices, these applications therefore suffer from significant performance problems, especially model loading and rendering problems. To this end, an AR-based multi-user BIM collaboration system, which can realise the on-demand dynamical loading of the BIM model by using the block-wise loading strategy of model transformation, thus solving the problem of model loading delay, was proposed. In addition, dynamic rendering technology is adopted to solve the problem of rendering lag. Experimental results show that the realisation of virtual-reality fusion and interaction for the BIM model and remote multi-user collaboration can effectively improve work efficiency and intelligence in the engineering field.
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Authentication scheme for industrial Internet of things based on DAG blockchain
Tang Fei, Dong Kun, Ye Zhangtao, Ling Guowei
The Journal of China Universities of Posts and Telecommunications    2021, 28 (6): 1-12.   DOI: 10. 19682 / j. cnki. 1005-8885. 2021. 1020
Abstract253)            Save
Internet of things ( IoT) can provide the function of product traceability for industrial systems. Emerging  blockchain technology can solve the problem that the current industrial Internet of things ( IIoT) system lacks  unified product data sharing services. Blockchain technology based on the directed acyclic graph (DAG) structure  is more suitable for high concurrency environments. But due to its distributed architecture foundation, direct storage  of product data will cause authentication problems in data management. In response, IIoT based on DAG  blockchain is proposed in this paper, which can provide efficient data management for product data stored on DAG  blockchain, and an authentication scheme suitable for this structure is given. The security of the scheme is based  on a discrete-logarithm-based assumption put forth by Lysyanskaya, Rivest, Sahai and Wolf(LRSW) who also show  that it holds for generic groups. The sequential aggregation signature scheme is more secure and efficient, and the  new scheme is safe in theory and it is more efficient in engineering.
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Liveness detection of occluded face based on dual-modality convolutional neural network
Ming Yue, Li Wenmin, Xu Siya, Gao Lifang, Zhang Hua, Shao Sujie, Yang Huifeng
The Journal of China Universities of Posts and Telecommunications    2021, 28 (4): 1-12.   DOI: 10.19682/j.cnki.1005-8885.2021.2001
Abstract250)            Save
Facial recognition has become the most common identity authentication technologies. However, problems such as  uneven light and occluded faces have increased the hardness of liveness detection. Nevertheless, there are a few  pieces of research on face liveness detection under occlusion conditions. This paper designs a face recognition  technique suitable for different degrees of facial occlusion, which employs the facial datasets of near-infrared (NIR)  images and visible (VIS) light images to examine the single-modality detection accuracy rate (experimental control  group) and the corresponding high-dimensional features through the residual network (ResNet). Based on the idea  of data fusion, we propose two feature fusion methods. The two methods extract and fuse the data of one and two  convolutional layers from two single-modality detectors respectively. The fusion of high-dimensional features apply a  new ResNet to get the dual-modality detection accuracy. And then, a new ResNet is applied to test the accuracy of  dual-modality detection. The experimental results show that the dual-modality face liveness detection model  improves face live detection accuracy and robustness compared with the single-modality. The fusion of two-layer  features from the single-modality detector can also improve face detection accuracy by utilizing the above-mentioned  dual-modality detector, and it doesn't increase the algorithm's complexity.
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Trusted data access and authorization protocol

The Journal of China Universities of Posts and Telecommunications    2021, 28 (5): 18-26.   DOI: 10. 19682 / j. cnki. 1005-8885. 2021. 0028
Abstract242)            Save

Threshold proxy re-encryption( PRE) authorizes the data access right of data subject to multiple proxies, who authorize the right again to delegatee to accomplish the end-to-end data encryption process from storage to authorization. Based on threshold PRE algorithm, in order to build a complete trusted data storage and authorization system, the four protocols, which are data access protocol, authorization proxy protocol, authorization proxy cancellation protocol and data reading authorization protocol, are defined completely. On that basis, an efficient data searching method is constructed by specifying the data delegatee. At last, to ensure the right to know of data, the audit log is processed with trusted data right confirmation based on distributed ledger technology. Meanwhile, a parallel data right confirmation processing method is defined based on hierarchical derivation algorithm of public and private key. In the end, the performance evaluation analysis of the protocol are given. Trusted data access and authorization protocol is convenient to build a complete data processing system on the premise of protecting data privacy based on public cloud storage system or distributed storage system.

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Design and implementation of labor arbitration system based on blockchain
Cui Hongyan CAI Ziyin Teng Shaokai
The Journal of China Universities of Posts and Telecommunications    2021, 28 (5): 36-45.   DOI: 10. 19682 / j. cnki. 1005-8885. 2021. 0032
Abstract217)            Save

Data island and information opacity are two major problems in collaborative administration. Blockchain has the potential to provide a trustable and transparent environment encouraging data sharing among administration members. However, the blockchain only stores Hash values and transactions in blocks which makes it unable to store big data and trace their changes. In this paper, a labor arbitration scheme based on blockchain was proposed to share labor arbitration data. In the system, a collaborative administration scheme that provides a big data storage model combined blockchain and interplanetary file system ( IPFS) is designed. It can store big data and share these data among different parties. Moreover, a file version control mechanism based on blockchain is designed to manage the data changes in IPFS network. It creates a tracing chain that consists of many IPFS objects to track changes of stored data. The relationship of previous and current IPFS objects recorded by blockchain can describe the changes of administration data and trace the data operations. The proposed platform is used in Rizhao City in China, and the experiment result shows collaborative administration scheme achieves traceability with high throughput and is more efficient than traditional hypertext transfer protocol ( HTTP) way to share data.

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Fine- grained cooperative access control scheme with hidden policies
Han Gang, Xing Qixuan, Zhang Yinghui
The Journal of China Universities of Posts and Telecommunications    2021, 28 (6): 13-25.   DOI: 10. 19682 / j. cnki. 1005-8885. 2021. 1021
Abstract216)            Save
The traditional ciphertext policy attribute-based encryption (CP-ABE) has two problems:one is that the access policy must be embedded in the ciphertext and sent, which leads to the disclosure of user爷 s privacy information, the other is that it does not support collaborative decryption, which cannot meet the actual demand of conditional collaborative decryption among multiple users. In order to deal with the above two problems at the same time, a fine-grained cooperative access control scheme with hidden policies (FCAC-HP) is proposed based on the existing CP-ABE schemes combined with blockchain technology. In FCAC-HP scheme, users are grouped by group identifier so that only users within the same group can cooperate. In the data encryption stage, the access policy is encrypted and then embedded in the ciphertext to protect the privacy information of the access policy. In the data access stage, the anonymous attribute matching technology is introduced so that only matched users can decrypt ciphertext data to improve the efficiency of the system. In this process, a smart contract is used to execute the
verification algorithm to ensure the credibility of the results. In terms of security, FCAC-HP scheme is based on the prime subgroup discriminative assumption and is proved to be indistinguishable under chosen plaintext attack (CPA) by dual system encryption technology. Experimental verification and analysis show that FCAC-HP scheme improves computational efficiency while implementing complex functions.
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Multi-level sharded blockchain system for edge computing

刘巧 唐碧华 Chen Xue Fan Wu 范文浩
The Journal of China Universities of Posts and Telecommunications    2021, 28 (5): 46-58.   DOI: 10. 19682 / j. cnki. 1005-8885. 2021. 0031
Abstract215)            Save

Blockchain technology is used in edge computing ( EC) systems to solve the security problems caused by single point of failure ( SPOF) due to data loss, task execution failure, or control by malicious nodes. However, the disadvantage of blockchain is high latency, which contradicts the strict latency requirements of EC services. The existing single-level sharded blockchain system ( SLSBS) cannot provide different quality of service for different tasks. To solve these problems, a multi-level sharded blockchain system ( MLSBS) based on genetic algorithm ( GA) is proposed. The shards are classified according to the delay of the service, and the parameters such as the shard size of different shards are different. Using the GA, the MLSBS obtains the optimal resource allocation strategy that achieves maximum security. Simulation results show that the proposed scheme outperforms SLSBS.


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Extensive game analysis and improvement strategy of DPOS consensus mechanism

The Journal of China Universities of Posts and Telecommunications    2021, 28 (5): 27-35.   DOI: 10. 19682 / j. cnki. 1005-8885. 2021. 0030
Abstract203)            Save

Delegated proof-of-stake ( DPOS) consensus mechanism is widely adopted in blockchain platforms, but problems exist in its current applications. In order to explore the security risks in the voting attack of the DPOS consensus mechanism, an extensive game model between nodes was constructed, and it was concluded that the DPOS consensus mechanism relies too much on tokens, and the possibility of node attacks is very high. In order to solve the problems of frequent changes of DPOS consensus mechanism nodes, inactive node voting, excessive reliance on tokens, and malicious nodes, a dynamic, credible, and attack-evading DPOS consensus mechanism was proposed. In addition, the Python simulation results show that the improved Bayesian voting algorithm is effective in calculating node scores.


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Exploring the usefulness of light field super-resolution for object detection
The Journal of China Universities of Posts and Telecommunications    2021, 28 (5): 68-81.   DOI: 10. 19682 / j. cnki. 1005-8885. 2021. 0023
Abstract195)            Save

In order to solve the impact of image degradation on object detection, an object detection method based on light field super-resolution ( LFSR) is proposed. This method takes LFSR as an image enhancement step to provide high- quality images for object detection without using expensive imaging equipment. To evaluate this method, three types of objects: person, bicycle, and car, are chosen and the results are compared from 5 parts: detected object quantity, mean confidence score, detection results in different scenes, error detection, and detection results from different images sizes and detection speed. Experimental results based on the common object in context ( COCO) dataset show that the method incorporated LFSR improves performance of object detection models.

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EPMDA: an efficient privacy-preserving multi-dimensional data aggregation scheme for edge computing-based IoT system
Tao Yunting, Kong Fanyu, Yu Jia
The Journal of China Universities of Posts and Telecommunications    2021, 28 (6): 26-35.   DOI: 10. 19682 / j. cnki. 1005-8885. 2021. 1022
Abstract182)            Save
In order to perform multi-dimensional data aggregation operations efficiently in edge computing-based Internet of things (IoT) systems, a new efficient privacy-preserving multi-dimensional data aggregation (EPMDA) scheme is proposed in this paper. EPMDA scheme is characterized by employing the homomorphic Paillier encryption and SM9 signature algorithm. To improve the computation efficiency of the Paillier encryption operation, EPMDA scheme generates a pre-computed modular exponentiation table of each dimensional data,and the Paillier encryption operation can be implemented by using only several modular multiplications. For the multi-dimensional data, the scheme concatenates zeros between two adjacent dimensional data to avoid data overflow in the sum operation of  ciphertexts. To enhance security, EPMDA scheme sets random number at the high address of the exponent. Moreover, the scheme utilizes SM9 signature scheme to guarantee device authentication and data integrity. The performance evaluation and comparison show that EPMDA scheme is more efficient than the existing multi-dimensional data aggregation schemes.
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Data-flow in mobile edge computing networks: end-to-end performance analysis using stochastic network calculus
Zhu Xiaorong, Jing Chuanfang, Shi Jindou, Wang Yong, Ho Chifong
The Journal of China Universities of Posts and Telecommunications    2022, 29 (1): 81-92.   DOI: 10.19682/j.cnki.1005-8885.2022.2009
Abstract176)            Save
Mobile edge computing (MEC) networks can provide a variety of services for different applications. End-to-end performance analysis of these services serves as a benchmark for the efficient planning of network resource allocation and routing strategies. In this paper, a performance analysis framework is proposed for the end-to-end data-flows in MEC networks based on stochastic network calculus (SNC). Due to the random nature of routing in MEC networks, probability parameters are introduced in the proposed analysis model to characterize this randomness into the derived expressions. Taking actual communication scenarios into consideration, the end-to-end performance of three network data-flows is analyzed, namely, voice over Internet protocol (VoIP), video, and file transfer protocol (FTP). These network data-flows adopt the preemptive priority scheduling scheme. Based on the arrival processes of these three data-flows, the effect of interference on their performances and the service capacity of each node in the MEC networks, closed-form expressions are derived for showing the relationship between delay, backlog upper bounds, and violation probability of the data-flows. Analytical and simulation results show that delay and backlog performances of the data-flows are influenced by the number of hops in the network and the random probability parameters of interference-flow (IF).
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Research on flame classification and recognition based on object detection and similarity fusion
The Journal of China Universities of Posts and Telecommunications    2021, 28 (5): 59-67.   DOI: 10. 19682 / j. cnki. 1005-8885. 2021. 0020
Abstract172)            Save

The color, shape, and other appearance characteristics of the flame emitted by different flame engines are different. In order to make a preliminary judgment on the category of the device to which it belongs through studying exterior characteristics of the flame, this paper uses the flame of matches, lighters, and candles to simulate different types of flames. It is hoped that the flames can be located and classified by detecting the characteristics of flames using the object detection algorithm. First, different types of fire are collected for the dataset of experiments. The mmDetection toolbox is then used to build several different object detection frameworks, in which the dataset can be trained and tested. The object detection model suitable for this kind of problem is obtained through the evaluation index analysis. The model is ResNet50-based faster-region-convolutional neural network ( Faster R- CNN), whose mean average-precision ( mAP) is 93.6% . Besides, after clipping the detected flames through object detection, a similarity fusion algorithm is used to aggregate and classify the three types of flames. Finally, the color components are analyzed to obtain the red, green, blue ( RGB) color histograms of the three flames.


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