A hologram, measured by using appropriate coherent illumination, records all substantial volumetric information of the measured sample. It is encoded in its interference patterns and, from these, the image of the sample objects can be reconstructed i...
Airborne hyperspectral data has high spectral-spatial information. However, how to mine and use this information effectively is still a great challenge. Recently, a three-dimensional convolutional neural network (3D-CNN) provides a new effective way...
Increasing attention has been paid to two-dimensional (2D) materials because of their superior performance and wafer-level synthesis methods. However, the large-area characterization, precision, intelligent automation, and high-efficiency detection o...
Accurate diagnosis of Parkinson’s disease (PD) is challenging in clinical medicine. To reduce the diagnosis time and decrease the diagnosis difficulty, we constructed a two-stream Three-Dimensional Convolutional Neural Network (3D-CNN) based on...
Water availability critically affects basil (Ocimum basilicum L.) growth and physiological performance, making the early and precise monitoring of water-deficit responses essential for precision irrigation. However, conventional visual or biochemical...
Cardiac function indices must be calculated using tracing from short-axis images in cine-MRI. A 3D-CNN (convolutional neural network) that adds time series information to images can estimate cardiac function indices without tracing using images with...
The recognition of emotions is one of the most challenging issues in human–computer interaction (HCI). EEG signals are widely adopted as a method for recognizing emotions because of their ease of acquisition, mobility, and convenience. Deep neu...
Drowsiness impairs drivers’ concentration and reaction time, doubling the risk of car accidents. Various methods for detecting drowsy driving have been proposed that rely on facial changes. However, they have poor detection for drivers wearing...
Researchers have explored various potential indicators of ASD, including changes in brain structure and activity, genetics, and immune system abnormalities, but no definitive indicator has been found yet. Therefore, this study aims to investigate ASD...
Video violence detection plays a crucial role in intelligent surveillance and public safety, yet existing methods still face challenges in modeling complex multi-person interactions. To address this, we propose IDG-ViolenceNet, a dual-stream video vi...
AI on spaceborne platforms optimizes operations and increases automation, crucial for satellites with limited downlink capacity. It can ensure that only valuable information is transmitted, minimizing resources spent on unnecessary data, which is esp...
The adulteration in Chinese chestnuts affects the quality, taste, and brand value. The objective of this study was to explore the feasibility of the hyperspectral imaging (HSI) technique to determine the geographical origin of Chinese chestnuts. An H...
The performance of near-field acoustic holography (NAH) with a sparse sampling rate will be affected by spatial aliasing or inverse ill-posed equations. Through a 3D convolution neural network (CNN) and stacked autoencoder framework (CSA), the data-d...
The precise identification, classification, sorting, and rapid and accurate quality assessment of soybean seeds are extremely important in terms of the continuity of agricultural production, varietal purity, seed processing, protein extraction, and f...
Since excessively worn tires pose a significant risk to vehicle safety, it is crucial to monitor tire wear regularly. This study aimed to verify the efficient tire wear prediction algorithm proposed in a previous modeling study, which minimizes the r...
Fault diagnosis (FD) plays a vital role in building a smart factory regarding system reliability improvement and cost reduction. Recent deep learning-based methods have been applied for FD and have obtained excellent performance. However, most of the...
Ground-penetrating radar (GPR) signal recognition depends much on manual feature extraction. However, the complexity of radar detection signals leads to conventional intelligent algorithms lacking sufficient flexibility in concrete pavement detection...
Lamb-wave-based structural health monitoring is widely employed to detect and localize damage in composite plates; however, interpreting Lamb wave signals remains challenging due to their dispersive characteristics. Although convolutional neural netw...
Among a series of video coding standards jointly developed by ITU-T, VCEG, and MPEG, high-efficiency video coding (HEVC) is one of the most widely used video coding standards today. Therefore, it is still necessary to further reduce the coding comple...
Convolutional neural networks provide an ideal solution for hyperspectral image (HSI) classification. However, the classification effect is not satisfactory when limited training samples are available. Focused on “small sample” hyperspect...
The combined application of machine or deep learning algorithms and hyperspectral imagery for bathymetry estimation is currently an emerging field with widespread uses and applications. This research topic still requires further investigation to achi...
As a promising alternative for cleaner vehicles, the growth of Battery Electric Vehicle (BEV) adoption should be supported by a reliable charging infrastructure. Therefore, projecting the charging load is required to ensure that the electricity suppl...
This study explores novel techniques to improve the detection accuracy of skarn iron deposits using advanced image-processing methodologies. Leveraging the capabilities of ASTER image, band ratio (BR) images, and principal component analysis (PCA) al...
Plastic greenhouses (PGs) are widely built near cities in China to produce vegetables and fruits. In order to promote sustainable agriculture, rural landscape construction, and better manage water resources, numerous remote sensing methods have been...
Internally mildewed sunflower seeds, which cannot be recognized and discarded based on their appearance, pose a serious risk to human health. Thus, there is a need for a rapid non-destructive mildew grade discrimination method. Currently, few reports...
Sunspots have a significant impact on human activities. In this study, we aimed to improve solar activity prediction accuracy. To predict the sunspot number based on different aspects, such as extracted features and relationships among data, we devel...
More efficient resource utilization and increased crop utilization rate are needed to address the growing demand for food. The efficient quality testing of key agricultural products such as potatoes, especially the rapid testing of key nutritional in...
The damaging effects of corona faults have made them a major concern in metal-clad switchgear, requiring extreme caution during operation. Corona faults are also the primary cause of flashovers in medium-voltage metal-clad electrical equipment. The r...
A method of direction-of-arrival (DoA) estimation for FMCW (Frequency Modulated Continuous Wave) radar is presented. In addition to MUSIC, which is the popular high-resolution DoA estimation algorithm, deep learning has recently emerged as a very pro...
Intelligent video analysis tools have advanced significantly, with numerous cameras installed in various locations to enhance security and monitor unusual events. However, the effective detection and monitoring of violent incidents often depend on ma...
This study presents a comprehensive exploration of the hyperparameter optimization in one-dimensional (1D) convolutional neural networks (CNNs) for network intrusion detection. The increasing frequency and complexity of cyberattacks have prompted an...
EEG-based emotion recognition has numerous real-world applications in fields such as affective computing, human-computer interaction, and mental health monitoring. This offers the potential for developing IOT-based, emotion-aware systems and personal...
Super-resolution (SR) is significant for hyperspectral image (HSI) applications. In single-frame HSI SR, how to reconstruct detailed image structures in high resolution (HR) HSI is challenging since there is no auxiliary image (e.g., HR multispectral...
As one of the most devastating disasters to pine forests, pine wilt disease (PWD) has caused tremendous ecological and economic losses in China. An effective way to prevent large-scale PWD outbreaks is to detect and remove the damaged pine trees at t...
With the continuous operation of analog circuits, the component degradation problem gradually comes to the forefront, which may lead to problems, such as circuit performance degradation, system stability reductions, and signal quality degradation, wh...
It is well known that power converters have the highest failure rate in the energy conversion chain in different industrial applications. This could definitely affect the reliability of the system. The reliability of converters in power conversion sy...
An equalizer based on a recurrent neural network (RNN), especially with a bidirectional gated recurrent unit (biGRU) structure, is a good choice to deal with nonlinear damage and inter-symbol interference (ISI) in optical communication systems becaus...
Early spring frost is a major meteorological hazard during the Apple Flowering period. To improve frost event prediction, this study proposes a hybrid 1D-CNN-BiLSTM-Attention model, with its core novelty lying in the integrated dual attention mechani...
Fluvial floods endure as one of the most catastrophic weather-induced disasters worldwide, leading to numerous fatalities each year and significantly impacting socio-economic development and the environment. Hence, the research and development of new...
Gastrodia elata (G. elata) Blume is widely used as a health product with significant economic, medicinal, and ecological values. Due to variations in the geographical origin, soil pH, and content of organic matter, the levels of physiologically activ...
Recently, hyperspectral image (HSI) classification using deep learning has been actively studied using 2D and 3D convolution neural networks (CNN). However, they learn spatial information as well as spectral information. These methods can increase th...
In existing proton exchange membrane fuel cell (PEMFC) applications, improper membrane water management will cause PEMFC performance decay, which restricts the reliability and durability of PEMFC systems. Therefore, diagnosing improper water content...
Unmanned aerial vehicle (UAV) based remote sensing is gaining momentum worldwide in a variety of agricultural and environmental monitoring and modelling applications. At the same time, the increasing availability of yield monitoring devices in harves...
The purpose of this study was to determine the feasibility of a deep convolutional neural network (dCNN) to accurately detect abnormal axillary lymph nodes on mammograms. In this retrospective study, 107 mammographic images in mediolateral oblique pr...
Gesture recognition has been applied in many fields as it is a natural human–computer communication method. However, recognition of dynamic gesture is still a challenging topic because of complex disturbance information and motion information....
Unintentional human falls, particularly in older adults, can result in severe injuries and death, and negatively impact quality of life. The World Health Organization (WHO) states that falls are a significant public health issue and the primary cause...
The diagnosis of a rolling bearing for monitoring its status is critical in maintaining industrial equipment while using rolling bearings. The traditional method of diagnosing faults of the rolling bearing has low identification accuracy, which needs...
Lung cancer is one of the most prevalent and deadly forms of cancer, accounting for a significant portion of cancer-related deaths worldwide. It typically originates in the lung tissues, particularly in the cells lining the airways, and early detecti...
Non-destructive assessment of kiwifruit quality is critical for postharvest preservation and grading. This paper proposes a novel quantitative evaluation method for the kiwifruit comprehensive quality index (KCQI) during shelf life, based on hyperspe...
Accurate estimation of chlorophyll content is essential for understanding the growth status and optimizing the cultivation practices of Ginkgo, a dominant multi-functional tree species in China. Traditional methods based on chemical analysis for dete...
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