Multi-source image fusion is very important for improving image representation ability since its essence relies on the complementarity between multi-source information. However, feature-level image fusion methods based on the convolution neural netwo...
In recent years, the field of multi-source navigation data fusion has witnessed substantial advancements, propelled by the rapid development of multi-sensor technologies, Artificial Intelligence (AI) algorithms and enhanced computational capabilities...
Multi-source information fusion technology is a kind of information processing technology which comprehensively processes and utilizes multi-source uncertain information. It is an effective scheme to solve complex pattern recognition and improve clas...
As we move into the information age, the amount of data in various fields has increased dramatically, and data sources have become increasingly widely distributed. The corresponding phenomenon of missing data is increasingly common, and it leads to t...
The development of material science in the manufacturing industry has resulted in a huge amount of material data, which are often from different sources and vary in data format and semantics. The integration and fusion of material data can offer a un...
Due to the rapid development of industrial internet technology, the traditional manufacturing industry is in urgent need of digital transformation, and one of the key technologies to achieve this is multi-source data fusion. For this problem, this pa...
Multi-source remote sensing image semantic segmentation can provide more detailed feature attribute information, making it an important research field for remote sensing intelligent interpretation. However, due to the complexity of remote sensing sce...
To address the issue of integrity monitoring for a multi-source information fusion navigation system, a theoretical framework of two-level integrity monitoring is proposed. Firstly, at the system level, a system-integrity-monitoring method based on t...
Benggangs, a type of soil erosion widely distributed in the hilly and mountainous regions of South China, pose significant challenges to land management and ecological conservation. Accurate identification and assessment of their location and scale a...
Rotating machinery is essential to modern industrial systems, where rolling bearings play a critical role in ensuring mechanical stability and operational efficiency. Failures in bearings can result in serious safety risks and significant financial l...
Multi-source data remote sensing provides innovative technical support for tree species recognition. Tree species recognition is relatively poor despite noteworthy advancements in image fusion methods because the features from multi-source data for e...
The leaf area index (LAI) is a critical biophysical parameter that reflects crop growth conditions and the canopy photosynthetic potential, serving as a cornerstone in precision agriculture and dynamic crop monitoring. However, traditional LAI estima...
For the state estimation problem of a multi-source localization nonlinear system with unknown and bounded noise, a distributed sequential ellipsoidal intersection fusion estimation algorithm based on the dual set-membership filtering method is propos...
The uncertainties in quality evaluations of rock mass are embedded in the underlying multi-source data composed by a variety of testing methods and some specialized sensors. To mitigate this issue, a proper method of data-driven computing for quality...
Efficient diagnosis of apple diseases and pests is crucial to the healthy development of the apple industry. However, the existing single-source image-based classification methods have limitations due to the constraints of single-source input image i...
Wood surface broken defects seriously damage the structure of wooden products, these defects have to be detected and eliminated. However, current defect detection methods based on machine vision have difficulty distinguishing the interference, simila...
High-resolution and high-quality precipitation data play an important role in Numerical Weather Prediction Model testing, mountain flood geological disaster monitoring, hydrological monitoring and prediction and have become an urgent need for the dev...
To address the limitations in predictive capabilities of thermal error models built from single-source, single-structure data, this paper proposes a thermal error prediction model based on decision-level fusion of multi-source heterogeneous informati...
In complex industrial processes such as sintering, key quality variables are difficult to measure online and it takes a long time to obtain quality variables through offline testing. Moreover, due to the limitations of testing frequency, quality vari...
With the rapid advancement of intelligent driving technology, multi-source information fusion has become a vital topic in the field of environmental perception. To address the fusion deviation resulting from changes in sensor performance due to envir...
Current research on evaluating tourism’s ecological efficiency using multi-source data fusion and graph neural networks has notable limitations. At the data level, integrating diverse sources is difficult due to differences in format, quality,...
Compared to traditional measurement devices, the micro-synchrophasor measurement unit (D-PMU or μPMU) in the distribution power system has great differences in data acquisition frequency, data format, data dimension, time-stamped information, etc....
Environment sensing plays an important role for the safe autonomous navigation of intelligent ships. However, the inherent limitations of sensors, such as the low frequency of the automatic identification system (AIS), blind zone of the marine radar,...
Accurate habitat prediction is important to improve fishing efficiency. Most of the current habitat-prediction studies use the single-source datasets and the sequence model based on single-source datasets, which, to a certain extent, limits the furth...
In additive manufacturing processes, the metal melt pool is decisive for processing quality. A single sensor is incapable of fully capturing its physical characteristics and is prone to data inaccuracies. This study proposes a multi-sensor monitoring...
Wind power forecasting is a typical high-dimensional and multi-step time series prediction problem. Data-driven prediction methods using machine learning show advantages over traditional physical or statistical methods, especially for wind farms with...
As intelligent mining develops, utilizing coal mine production monitoring data for early warnings has become a crucial means of ensuring safety in mining operations. Assisting decision-makers in making scientific choices through multi-source and mass...
The museum system is exposed to a high risk of seismic hazards. However, it is difficult to carry out seismic hazard prevention to protect cultural relics in collections due to the lack of real data and diverse types of seismic hazards. To address th...
The existing motor fault classification methods mostly use sensors to detect a single fault feature, which makes it difficult to ensure high diagnostic accuracy. In this paper, a motor fault classification method based on multi-source information fus...
Dempster–Shafer (DS) evidence theory is widely applied in multi-source data fusion technology. However, classical DS combination rule fails to deal with the situation when evidence is highly in conflict. To address this problem, a novel multi-s...
Aiming to mitigate engineering risks such as tunnel face collapse and equipment jamming caused by poor geological conditions during the construction of tunnel boring machines (TBMs), this study proposes a TBM surrounding rock grade prediction method...
The operating environment of the shielding sleeve of the main pump motor is complex and changeable, and it is affected by various stresses; so, it is prone to bulging, cracking, and wear failure. The space where it is located is narrow, making it dif...
Time-series Interferometric Synthetic Aperture Radar (InSAR) techniques encounter substantial reliability challenges, primarily due to the presence of gross errors arising from phase unwrapping failures. These errors propagate through the processing...
In order to improve the detection accuracy for the quality of wheat, a recognition method for wheat quality using the terahertz (THz) spectrum and multi-source information fusion technology is proposed. Through a combination of the absorption and the...
Soil organic matter (SOM) content is a key indicator for assessing soil health, carbon cycling, and soil degradation. Traditional SOM detection methods are complex and time-consuming and do not meet the modern agricultural demand for rapid, non-destr...
Synthetic Aperture Radar Interferometry (InSAR) has demonstrated significant advantages in detecting active landslides. The proliferation of computing technology has enabled the combination of InSAR and deep learning, offering an innovative approach...
In modern industries, bearings are often subjected to challenges from environmental noise and variations in operating conditions during their operation, which affects existing fault diagnosis methods that rely on signals from single types of sensors....
Dempster–Shafer evidence theory is widely used in modeling and reasoning uncertain information in real applications. Recently, a new perspective of modeling uncertain information with the negation of evidence was proposed and has attracted a lo...
Aphids are the main agricultural pests that affect the quality and yield of peppers in the greenhouse. Efficient early prediction of aphid occurrence is of great significance for the development of digitization and information technology in intellige...
Collapse is the main engineering disaster in tunnel construction when using the drilling and blasting method, and risk assessment is one of the important means to significantly reduce engineering disasters. Aiming at the problems of random decision-m...
Multi-source information fusion is widely used because of its similarity to practical engineering situations. With the development of science and technology, the sources of information collected under engineering projects and scientific research are...
Deep learning (DL) has been widely used to promote the development of intelligent fault diagnosis, bringing significant performance improvement. However, most of the existing methods cannot capture the temporal information and global features of mech...
Nitrogen (N) is an important factor limiting crop productivity, and accurate estimation of the N content in winter wheat can effectively monitor the crop growth status. The objective of this study was to evaluate the ability of the unmanned aerial ve...
In the context of the booming construction of smart cities, multi-source data fusion and analysis algorithms play a key role in optimizing real estate management and improving urban efficiency. In this review, we comprehensively and systematically re...
Positioning information greatly enhances the convenience of people’s lives and the efficiency of societal operations. However, due to the impact of complex indoor environments, GNSS signals suffer from multipath effects, blockages, and attenuat...
Accurate remaining useful life (RUL) prediction of rolling bearings plays a critical role in predictive maintenance. However, existing methods face challenges in extracting and fusing multi-source spatiotemporal features, addressing distribution diff...
In this paper, a lightweight, high-definition mapping method is proposed for autonomous driving to address the drawbacks of traditional mapping methods, such as high cost, low efficiency, and slow update frequency. The proposed method is based on mul...
In multi-source fusion deformation-monitoring methods that utilize fiber Bragg grating (FBG) data and other data types, the lack of FBG constraint points in edge regions often results in inaccuracies in fusion results, thereby impacting the overall d...
Floods have significant impacts on economic development and cause the loss of both lives and property, posing a serious threat to social stability. Effectively identifying the evolution patterns of floods could enhance the role of flood monitoring in...
A radar is an important part of an air defense and combat system. It is of great significance to military defense to improve the effectiveness of radar state monitoring and the accuracy of fault diagnosis during operation. However, the complexity of...
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