-
CiteScore
1.83
Impact Factor
Latest Issue
Volume 1, Issue 2
Chinese Journal of Information Fusion
  ISSN:  2998-3371 (online)  |  2998-3363 (print)
Editors-in-Chief:  You He,  Jun Lu
Impact Factor (Google): 1.83
CiteScore: -
Indexing: Google Scholar, Dimensions, Lens, ResearchGate, OpenAlex, WorldCat
Chinese Journal of Information Fusion is a peer-reviewed international academic journal reflecting the achievements of cutting-edge research and application of information fusion technology, mainly publishing academic papers in the field of information fusion.
E-mail:[email protected]  DOI Prefix: 10.62762/CJIF
12
Total Articles
22
Citations
20542
Article Views

Recent Articles

Free Access | Research Article | 30 September 2024
Unsupervised Industrial Anomaly Detection Based on Feature Mask Generation and Reverse Distillation
Chinese Journal of Information Fusion | Volume 1, Issue 2: 160-174, 2024 | DOI:10.62762/CJIF.2024.734267
Abstract
In the realm of industrial defect detection, unsupervised anomaly detection methods draw considerable attention as a result of their exceptional accomplishments. Among these, knowledge distillation-based methods have emerged as a prominent research focus, favored for their streamlined architecture, precision, and efficiency. However, the challenge of characterizing the variability in anomaly samples hinders the accuracy of detection. To address this issue, our research presents a novel approach for anomaly detection and localization, leveraging the concept of inverse knowledge distillation as its cornerstone. We employ the encoder as the guiding teacher model and designate the decoder as the... More >

Graphical Abstract
Unsupervised Industrial Anomaly Detection Based on Feature Mask Generation and Reverse Distillation

Free Access | Review Article | Feature Paper | 30 September 2024
Complex Evidence Theory for Multisource Data Fusion
Chinese Journal of Information Fusion | Volume 1, Issue 2: 134-159, 2024 | DOI:10.62762/CJIF.2024.999646
Abstract
Data fusion is a prevalent technique for assembling imperfect raw data coming from multiple sources to capture reliable and accurate information. Dempster–Shafer evidence theory is one of useful methodologies in the fusion of uncertain multisource information. The existing literature lacks a thorough and comprehensive review of the recent advances of Dempster– Shafer evidence theory for data fusion. Therefore, the state of the art has to be surveyed to gain insight into how Dempster–Shafer evidence theory is beneficial for data fusion and how it evolved over time. In this paper, we first provide a comprehensive review of data fusion methods based on Dempster–Shafer evidence theory an... More >

Graphical Abstract
Complex Evidence Theory for Multisource Data Fusion

Free Access | Research Article | 29 September 2024
Explainable Classification of Remote Sensing Ship Images Based on Graph Network
Chinese Journal of Information Fusion | Volume 1, Issue 2: 126-133, 2024 | DOI:10.62762/CJIF.2024.932552
Abstract
Remote sensing image plays an important role in maritime surveillance, and as a result there is increasingly becoming a prominent focus on the detection and recognition of maritime objects. However, most existing studies in remote sensing image classification pay more attention on the performance of model, thus neglecting the transparency and explainability in it. To address the issue, an explainable classification method based on graph network is proposed in the present study, which seeks to make use of the relationship between objects' regions to infer the category information. First, the local visual attention module is designed to focus on different but important regions of the object. T... More >

Graphical Abstract
Explainable Classification of Remote Sensing Ship Images Based on Graph Network

Free Access | Research Article | 27 September 2024
A High-Efficiency Two-Layer Path Planning Method for UAVs in Vast Airspace
Chinese Journal of Information Fusion | Volume 1, Issue 2: 109-125, 2024 | DOI:10.62762/CJIF.2024.596648
Abstract
In response to the challenges associated with the inefficiency and poor quality of 3D path planning for Unmanned Aerial Systems (UAS) operating in vast airspace, a novel two-layer path planning method is proposed based on a divide-and-conquer methodology. This method segregates the solution process into two distinct stages: heading planning and path planning, thereby ensuring the planning of both efficiency and path quality. Firstly, the path planning phase is formulated as a multi-objective optimization problem, taking into account the environmental constraints of the UAV mission and path safety. Subsequently, the multi-dimensional environmental data is transformed into a two-dimensional pr... More >

Graphical Abstract
A High-Efficiency Two-Layer Path Planning Method for UAVs in Vast Airspace

Free Access | Research Article | 23 September 2024
Convolutional Neural Network for Ellipse Extended Target Tracking
Chinese Journal of Information Fusion | Volume 1, Issue 2: 93-108, 2024 | DOI:10.62762/CJIF.2024.160538
Abstract
In the field of extended target tracking, constrained by the sparse measurement set from radar, the target contour is commonly estimated as an elliptical shape. This paper uses convolutional neural networks to estimate the size and orientation information of extended targets. First, by establishing a systematic model for elliptical extended targets and modeling its measurement information, data normalization, and length equalization operations were conducted to provide reliable measurement data for subsequent neural network processing. Subsequently, through the construction of a convolutional neural network model, accurate estimation of the contour parameters of elliptical extended targets w... More >

Graphical Abstract
Convolutional Neural Network for Ellipse Extended Target Tracking

Free Access | Review Article | 12 June 2024 | Cited: 1
Bridging Modalities: A Survey of Cross-Modal Image-Text Retrieval
Chinese Journal of Information Fusion | Volume 1, Issue 1: 79-92, 2024 | DOI:10.62762/CJIF.2024.361895
Abstract
The rapid advancement of Internet technology, driven by social media and e-commerce platforms, has facilitated the generation and sharing of multimodal data, leading to increased interest in efficient cross-modal retrieval systems. Cross-modal image-text retrieval, encompassing tasks such as image query text (IqT) retrieval and text query image (TqI) retrieval, plays a crucial role in semantic searches across modalities. This paper presents a comprehensive survey of cross-modal image-text retrieval, addressing the limitations of previous studies that focused on single perspectives such as subspace learning or deep learning models. We categorize existing models into single-tower, dual-tower,... More >

Graphical Abstract
Bridging Modalities: A Survey of Cross-Modal Image-Text Retrieval

Free Access | Research Article | Feature Paper | 10 June 2024 | Cited: 2
Extraction of Motion Information from Occupancy Grid Map Using Keystone Transform
Chinese Journal of Information Fusion | Volume 1, Issue 1: 63-78, 2024 | DOI:10.62762/CJIF.2024.361892
Abstract
Considering the tractability of OGM (Occupancy Grid Map) and its wide use in the dynamic environment representation of mobile robotics, the extraction of motion information from successive OGMs are very important for many tasks, such as SLAM (Simultaneously Localization And Mapping) and DATMO (Detection and Tracking of Moving Object). In this paper, we propose a novel motion extraction method based on the signal transform, called as S-KST (Spatial Keystone Transform), for the motion detection and estimation from successive noisy OGMs. It extends the KST in radar imaging or motion compensation to 1D spatial case (1DS-KST) and 2D spatial case (2DS-KST) combined multiple hypotheses about poss... More >

Graphical Abstract
Extraction of Motion Information from Occupancy Grid Map Using Keystone Transform

Free Access | Research Article | 08 June 2024
GPS Tracking Based on Stacked-Serial LSTM Network
Chinese Journal of Information Fusion | Volume 1, Issue 1: 50-62, 2024 | DOI:10.62762/CJIF.2024.361889
Abstract
Maneuvering target tracking is widely used in unmanned vehicles, missile navigation, underwater ships, etc. Due to the uncertainty of the moving characteristics of maneuvering targets and the low sensor measurement accuracy, trajectory tracking has always been an open research problem and challenging work. This paper proposes a trajectory estimation method based on LSTM neural network for uncertain motion characteristics. The network consists of two LSTM networks with stacked serial relationships, one of which is used to predict the movement dynamics, and the other is used to update the track's state. Compared with the classical Kalman filter based on the maneuver model, the method proposed... More >

Graphical Abstract
GPS Tracking Based on Stacked-Serial LSTM Network

Author's Talk | Free Access | Research Article | Feature Paper | 28 May 2024 | Cited: 6
A Mimic Fusion Algorithm for Dual Channel Video Based on Possibility Distribution Synthesis Theory
Chinese Journal of Information Fusion | Volume 1, Issue 1: 33-49, 2024 | DOI:10.62762/CJIF.2024.361886
Abstract
In response to the current practical fusion requirements for infrared and visible videos, which often involve collaborative fusion of difference feature information, and model cannot dynamically adjust the fusion strategy according to the difference between videos, resulting in poor fusion performance, a mimic fusion algorithm for infrared and visible videos based on the possibility distribution synthesis theory is proposed. Firstly, quantitatively describe the various difference features and their attributes of the region of interest in each frame of the dual channel video sequence, and select the main difference features corresponding to each frame. Secondly, the pearson correlation coeffi... More >

Graphical Abstract
Author's Talk
A Mimic Fusion Algorithm for Dual Channel Video Based on Possibility Distribution Synthesis Theory
A Mimic Fusion Algorithm for Dual Channel Video Based on Possibility Distribution Synthesis Theory

Free Access | Research Article | Feature Paper | 27 May 2024 | Cited: 4
Simultaneous Spatiotemporal Bias Compensation and Data Fusion for Asynchronous Multisensor Systems
Chinese Journal of Information Fusion | Volume 1, Issue 1: 16-32, 2024 | DOI:10.62762/CJIF.2024.361881
Abstract
Bias estimation of sensors is an essential prerequisite for accurate data fusion. Neglect of temporal bias in general real systems prevents the existing algorithms from successful application. In this paper, both spatial and temporal biases in asynchronous multisensor systems are investigated and two novel methods for simultaneous spatiotemporal bias compensation and data fusion are presented. The general situation that the sensors sample at different times with different and varying periods is explored, and unknown time delays may exist between the time stamps and the true measurement times. Due to the time delays, the time stamp interval of the measurements from different sensors may be di... More >

Graphical Abstract
Simultaneous Spatiotemporal Bias Compensation and Data Fusion for Asynchronous Multisensor Systems

Free Access | Research Article | 25 May 2024 | Cited: 3
Research on A Ship Trajectory Classification Method Based on Deep Learning
Chinese Journal of Information Fusion | Volume 1, Issue 1: 3-15, 2024 | DOI:10.62762/CJIF.2024.361873
Abstract
The unrestricted development and utilization of marine resources have resulted in a series of practical problems, such as the destruction of marine ecology. The wide application of radar, satellites and other detection equipment has gradually led to a large variety of large-capacity marine spatiotemporal trajectory data from a vast number of sources. In the field of marine domain awareness, there is an urgent need to use relevant information technology means to control and monitor ships and accurately classify and identify ship behavior patterns through multisource data fusion analysis. In addition, the increase in the type and quantity of trajectory data has produced a corresponding increa... More >

Graphical Abstract
Research on A Ship Trajectory Classification Method Based on Deep Learning

Open Access | Editorial | 23 May 2024
Inaugural Editorial of the Chinese Journal of Information Fusion
Chinese Journal of Information Fusion | Volume 1, Issue 1: 1-2, 2024 | DOI:10.62762/CJIF.2024.100001
Abstract
Presents the introductory editorial for this issue of the publication. More >
Chinese Journal of Information Fusion

Chinese Journal of Information Fusion

ISSN: 2998-3371 (Online) | ISSN: 2998-3363 (Print)

Email: [email protected]

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