The analysis of historical pigments contributes significantly to understanding the materials and techniques used in artworks and in preserving cultural heritage. This work introduces a novel methodology for classifying historical pigments combining X...
A rolling element signal has a long transmission path in the acquisition process. The fault feature of the rolling element signal is more difficult to be extracted. Therefore, a novel weak fault feature extraction method using optimized variational m...
The fault diagnosis of rolling element bearing is of great significance to avoid serious accidents and huge economic losses. However, the characteristics of the nonlinear, non-stationary vibration signals make the fault feature extraction of signal b...
Lettuce is one of the most widely planted leafy vegetables in plant factories. The lack of trace elements in nutrient solutions has caused huge losses to the lettuce industry. Non-obvious symptoms of trace element deficiency, the inconsistent size of...
For early fault detection of a bearing, the localized defect generally brings a complex vibration signal, so it is difficult to detect the periodic transient characteristics from the signal spectrum using conventional bearing fault diagnosis methods....
Extracting road from high resolution remote sensing (HRRS) images is an economic and effective way to acquire road information, which has become an important research topic and has a wide range of applications. In this paper, we present a novel metho...
Image low-level information, such as color, texture, and shape, were generally dealt with separately and combined together gruffly. Their image-describing effect in image retrieval was weakened. This paper determines and extracts one group of texture...
This paper proposes a feature extraction method based on information theory for fault diagnosis of reciprocating machinery. A method to obtain symptom parameter waves is defined in the time domain using the vibration signals, and an information wave...
Fatalities and serious injuries still represent a significant portion of run-off-the-road (ROR) collisions on highways in North America. In order to address this issue and design safer and more forgiving roadside areas, more empirical evidence is req...
Bearing component damage contributes significantly to rotating machinery failures. It is vital for the rotor-bearing system to be in good condition to ensure the proper functioning of the machine. Over recent decades, extensive research has been devo...
In order to extract and enhance the weak fault feature of rolling element bearings in strong noise conditions, the Empirical Wavelet Transform (EWT) is improved and a novel fault feature extraction and enhancement method is proposed by combining the...
Insufficient color feature extraction can lead to poor prediction performance in rare earth element composition estimation. To address this issue, we propose a one-dimensional convolutional method for predicting rare earth element composition. First,...
In the context of the information age, the symbolization of regional elements has become a crucial component in modern cartographic practice. The targeted identification of regional elements and the design of map symbols are prerequisites for realizi...
Accurately extracting network security situation elements is an important basis for improving the situational awareness of industrial Internet security. This paper proposes an industrial internet security situation element extraction algorithm based...
Forest management planning in Finland is currently adopting a new-generation forest inventory method, which is based on interpretation of airborne laser scanning data and digital aerial images. The inventory method is based on a systematic grid, wher...
Recently, the transformer model has progressed from the field of visual classification to target tracking. Its primary method replaces the cross-correlation operation in the Siamese tracker. The backbone of the network is still a convolutional neural...
To address the problem of low accuracy in line element recognition of raster maps due to text and background interference, we propose a raster map line element recognition method based on an improved U-Net network model, combining the semantic segmen...
Recently, the rapid development of multispectral imaging technology has received great attention from many fields, which inevitably involves the image transmission and storage problem. To solve this issue, a novel end-to-end multispectral image compr...
This research aims to develop an unsupervised machine learning technique for ball bearing fault detection and fault diagnosis. It evaluates vibration signals through Autoregression (AR) models and Fuzzy C-means (FCM) clustering for experimental data...
The extraction of shape features from vector elements is essential in cartography and geographic information science, supporting a range of intelligent processing tasks. Traditional methods rely on different machine learning algorithms tailored to sp...
Knowledge graph embedding is a method to predict missing links in knowledge graphs by learning the interactions between embedded entities and relations in a continuous low-dimensional space. Current research on convolution-based models tends to provi...
Feature line extraction for building roofs is a critical step in the 3D model reconstruction of buildings. A feature line extraction algorithm for building roof point clouds based on the linear distribution characteristics of neighborhood points was...
Riverbed micro-topographical features, such as crest and trough, flat bed, and scour pit, indicate the evolution of fluvial geomorphology, and have an influence on the stability of underwater structures and overall scour pits. Previous studies on bed...
The accurate localization of the rolling element failure is very important to ensure the reliability of rotating machinery. This paper proposes an efficient and anti-noise fault diagnosis model for rolling elements. The proposed model is composed of...
In view of the poor performance of traditional feature point detection methods in low-texture situations, we design a new self-supervised feature extraction network that can be applied to the visual odometer (VO) front-end feature extraction module b...
Unauthenticated device access to a network presents substantial security risks. To address the challenges of access and identification for a vast number of devices with diverse functions in the era of the Internet of things (IoT), we propose an IoT d...
Finite element model updating precision depends heavily on sufficient vibration feature extraction. However, adequate amount of sample collection is generally time-consuming in frequency response (FR) model updating. Accurate vibration feature extrac...
In this paper, we demonstrate that fixed-weight layers generated from random distribution or logistic functions can effectively extract significant features from input data, resulting in high accuracy on a variety of tasks, including Fisher’s I...
Step-feature lines are one of the important geometrical elements for drawing the status quo maps of open-pit mines, and the efficient and accurate automatic extraction and updating of step-feature lines is of great significance for open-pit-mine stri...
Visible image quality is very susceptible to changes in illumination, and there are limitations in ship classification using images acquired by a single sensor. This study proposes a ship classification method based on an attention mechanism and mult...
Accurate wind speed prediction plays a crucial role in wind power generation and disaster avoidance. However, stochasticity and instability increase the difficulty of wind speed prediction. In this study, we proposed a dual-attention mechanism multi-...
Aiming at the limitations of a single High Resolution Range Profile (HRRP) in recognition, this paper proposes a Time step Correlation-based Feature Fusion (TCFF) method. This method calculates the covariance matrix at the time step of the two featur...
This paper proposes an emotion recognition method for tweets containing emoticons using their emoticon image and language features. Some of the existing methods register emoticons and their facial expression categories in a dictionary and use them, w...
The use of digital technologies in Product Service Systems (PSSs) has increased in recent years. More and more smart devices are used in these models, collecting significant amounts of data to provide personalized and responsive products and services...
To promote the inheritance of Zhuang brocade culture and the rapid extraction of features and automatic generation of patterns, this paper constructs a feature dataset of Zhuang brocade patterns and proposes an automatic generation technology using r...
Most traditional hyperspectral image (HSI) classification methods relied on hand-crafted or shallow-based descriptors, which limits their applicability and performance. Recently, deep learning has gradually become the mainstream method of HSI classif...
Speciation analysis is a relevant topic since the (eco)toxicity, bioavailability, bio (geo)chemical cycles, and mobility of a given element depend on its chemical forms (oxidation state, organic ligands, etc.). The reliability of analytical results f...
In complex environments such as those with low textures or obvious brightness changes, point features extracted from a traditional FAST algorithm cannot perform well in pose estimation. Simultaneously, the number of point features extracted from FAST...
X-ray fluorescence (XRF) spectroscopy is a non-destructive differential measurement technique widely utilized in elemental analysis. However, due to its inherent high non-linearity and noise issues, it is challenging for XRF spectral analysis to achi...
The application of AR to explore augmented map representation has become a research hotspot due to the growing application of AR in maps and geographic information in addition to the rising demand for automated map interpretation. Taking the AR map a...
In biometrics, it is desirable to distinguish a person using only a short sample of his handwriting. This problem is treated in the present work using only a short word with three letters. It is shown that short words can contribute to high-performan...
Deep learning is an important research topic in the field of image super-resolution. Problematically, the performance of existing hyperspectral image super-resolution networks is limited by feature learning for hyperspectral images. Nevertheless, the...
Bearings are not only the most important element but also a common source of failures in rotary machinery. Bearing fault prognosis technology has been receiving more and more attention recently, in particular because it plays an increasingly importan...
This paper proposes a framework to extract knowledge-management elements from business systems in healthcare organizations. According to results of in-depth interviews with experts in the field, a framework is defined, and software was developed to g...
The abnormal wear of a rolling element bearing caused by early failures, such as pitting and spalling, will deteriorate the running state and reduce the life. This paper demonstrates the importance of oil debris monitoring and its effective feature e...
Chinese olive trees (Canarium album L.) are broad-leaved species that are widely planted in China. Accurately obtaining tree crown information provides important data for evaluating Chinese olive tree growth status, water and fertilizer management, a...
Subsurface structural distribution can be detected using Ground-Penetrating Radar (GPR). The distribution can be considered as road fingerprints for vehicle positioning. Similar to the principle of visual image matching for localization, the position...
Conventional ship detection using synthetic aperture radar (SAR) is typically limited to fully focused spatial features of the ship target in SAR images. In this paper, we propose a multi-stage feature transfer (MFT)-based reasoning RCNN (MFT-Reasoni...
Image recognition and classification have been widely used for research in computer vision systems. This paper aims to implement a new strategy called Wiener-Granger Causality theory for classifying natural scenery images. This strategy is based on s...
Action recognition requires the accurate analysis of action elements in the form of a video clip and a properly ordered sequence of the elements. To solve the two sub-problems, it is necessary to learn both spatio-temporal information and the tempora...
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