With growing consumer concerns about food safety, developing methods for the field-based, non-destructive, and rapid detection of pesticide residues is becoming increasingly critical. This study introduces a field-based, non-destructive, and rapid me...
This study presents a 1D Residual Network(ResNet)-based algorithm for human activity recognition (HAR) focused on classifying 14 different workouts, which represent key exercises commonly performed in fitness training, using wearable inertial measure...
Strong broadband noise can mask the weak impact responses produced by bearing faults, while wavelet reconstructions selected only by signal-domain scores may not provide useful inputs for diagnosis. To address this problem, this paper presents WPMSR-...
Rolling element bearing fault diagnosis (BFD) is fundamental to Predictive Maintenance (PdM) strategies for rotating machinery, as early anomaly detection prevents catastrophic failures, reduces unplanned downtime, and optimizes operational costs. Th...
Ensuring food security in precision agriculture requires early prediction of soybean yield at various scales within the United States (U.S.), ranging from international to local levels. Accurate yield estimation is essential in preventing famine by p...
This work presents a lightweight and practical methodology for detecting inter-turn short-circuit faults in squirrel-cage induction motors under different mechanical load conditions. The proposed approach utilizes a one-dimensional convolutional neur...
An animal’s emotion is regarded as a critical indicator for assessing its welfare. At present, most canine emotion recognition models rely on static images, which leads to insufficient modeling of spatiotemporal features and low accuracy. To ad...
Accurate prediction of soybean yield is important for safeguarding food security and improving agricultural management. Recent advances have highlighted the effectiveness and ability of Machine Learning (ML) models in analyzing Remote Sensing (RS) da...
The distributed denial of service (DDoS) vulnerabilities have rapidly extended and have been given different possibilities for even more advanced assaults on specific targets in recent times, thanks to the growth of innovative technology such as the...
In recent years, the research into automatic aided detection systems for pulmonary nodules has been extremely active. Most of the existing studies are based on 2D convolution neural networks, which cannot make full use of computed tomography’s (CT) 3...
Gentian is a traditional Chinese herb with heat-clearing, damp-drying, inflammation-alleviating and digestion-promoting effects, which is widely used in clinical practice. However, there are many species of gentian. According to the pharmacopoeia, Ge...
Personal identification is an important aspect of managing electronic health records (EHRs), ensuring secure access to patient information, and maintaining patient privacy. Traditionally, biometric, signature, username/password, photo identity, etc.,...
In order to better predict the high aerosol concentrations associated with air pollution and climate change, a machine learning model was developed using transfer learning and the segmentation process of global satellite images. The main concept of t...
Video violence detection has gained significant attention in recent years due to its applications in surveillance and security. This paper proposes a two-stage framework for detecting violent actions in video sequences. The first stage leverages GMFl...
Dry gas seals are widely used in the petrochemical industry for shaft end sealing of compressors, pumps and other equipment involving flammable, explosive, toxic and harmful media. To address the challenge of accurately identifying the fault states o...
Tool wear is a key factor in the machining process, which affects the tool life and quality of the machined work piece. Therefore, it is crucial to monitor and diagnose the tool condition. An improved CaAt-ResNet-1d model for multi-sensor tool wear d...
Sign language is a complex and dynamic visual language that requires the coordinated movement of various body parts, such as the hands, arms, and limbs—making it an ideal application domain for sensor networks to capture and interpret human ges...
Amid the ongoing emphasis on reducing manufacturing costs and enhancing productivity, one of the crucial objectives when manufacturing is to maintain process tools in optimal operating conditions. With advancements in sensing technologies, large amou...
Ubiquitous radar has significant advantages over traditional radar in detecting and identifying low, slow, and small (LSS) targets in a strong clutter environment. It effectively addresses challenges faced in low-altitude target monitoring within the...
This paper studies various deep learning models for word-level lip-reading technology, one of the tasks in the supervised learning of video classification. Several public datasets have been published in the lip-reading research field. However, few st...
This work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary pa...
Blink detection is considered a useful indicator both for clinical conditions and drowsiness state. In this work, we propose and compare deep learning architectures for the task of detecting blinks in video frame sequences. The first step is the trai...
Retention of rice freshness is highly dependent on storage temperature. Timely and accurate identification of rice freshness is critical to ensure food security. Here, we characterize the freshness of rice in reference to storage temperature. Teraher...
Human action recognition is a constantly evolving field that is driven by numerous applications. In recent years, significant progress has been made in this area due to the development of advanced representation learning techniques. Despite this prog...
This paper proposes a method for automatic pig detection and segmentation using RGB-D data for precision livestock farming. The proposed method combines the enhanced YOLOv5s model with the Res2Net bottleneck structure, resulting in improved fine-grai...
This study proposes a three-dimensional (3D) residual attention network (3DRFNet) for human activity recognition by learning spatiotemporal representations from motion pictures. Core innovation integrates the attention mechanism into the 3D ResNet fr...
Lung cancer is by far the leading cause of cancer death among both men and women, making up almost 25% of all cancer deaths Each year, more people die of lung cancer than colon, breast, and prostate cancer combined. The early detection of lung cancer...
Currently, medical imaging has largely supplanted traditional methods in the realm of diagnosis and treatment planning. This shift is primarily attributable to the non-invasive nature, rapidity, and user-friendliness of medical-imaging techniques. Th...
Automated quality control is critical in modern manufacturing, especially for metallic cast components, where fast and accurate surface defect detection is required. This study evaluates classical Machine Learning (ML) algorithms using extracted stat...
The clinical translation of automated HPV detection in Whole Slide Images (WSIs) is challenged by staining variability, sparse viral effects, and the biological continuum between cytology and histology. This work presents a fully automated pipeline f...
Timely and accurate urban change detection is vital for sustainable urban development, infrastructure management, and disaster response. Traditional two-dimensional approaches often overlook vertical and structural variations in dense urban areas. Th...
Low-count positron emission tomography (PET) is inherently affected by Poisson-dominated noise, which degrades image contrast, structural delineation, and quantitative reliability. This study systematically evaluated residual learning-based deep neur...
Point cloud segmentation, as the basis for 3D scene understanding and analysis, has made significant progress in recent years. Graph-based modeling and learning methods have played an important role in point cloud segmentation. However, due to the in...
Deepfake detection has become a critical issue due to the rise of synthetic media and its potential for misuse. In this paper, we propose a novel approach to deepfake detection by combining video frame analysis with facial microexpression features. T...
Lipreading aims to recognize sentences being spoken by a talking face. In recent years, the lipreading method has achieved a high level of accuracy on large datasets and made breakthrough progress. However, lipreading is still far from being solved,...
Deepfakes threaten sensor-based authentication systems, including biometric sensors, surveillance cameras, and IoT edge devices. Unimodal detectors remain vulnerable to modality-specific attacks. We propose a multimodal deepfake detection framework o...
Layer thickness uniformity critically influences the dimensional accuracy and mechanical performance of large-scale cementitious structures produced by material extrusion 3D printing. This study introduces a computer vision workflow that couples trad...
Deep-learning models for computed tomography (CT) analysis are usually released as training scripts and weight files rather than as tools a clinician can open and run, and many of them assume a GPU, a network connection or a commercial licence. We de...
Recent studies in transillumination imaging for developing an optical computed tomography device for small animal and human body parts have used deep learning networks to suppress the scattering effect, estimate depth information of light-absorbing s...
A WGAN-GP-based ECG signal expansion and an SE-ResNet1D-based ECG classification method are proposed to address the problem of poor modeling results due to the imbalanced sample distribution of ECG data sets. The network architectures of WGAN-GP and...
Acoustic propagation in stratified shallow seas is governed by finite-depth waveguiding, impedance contrasts at the seawater–seabed interface, and coupled space–time wave dynamics. Conventional numerical solvers are accurate but often req...
Pediatric craniofacial fractures represent a significant diagnostic challenge due to age-dependent anatomical variability, subtle fracture lines, and the limited availability of specialists during emergency care. Computed tomography (CT) remains the...
Digital histology of human postmortem brain tissue is fundamental to understanding neurodegeneration, yet resolving the spatial organisation of neuroinflammatory markers remains challenging because manual scoring and scalar summaries capture only par...
Moving target detection in optical remote sensing is important for satellite surveillance and space target monitoring. Here, a new moving point target detection framework under a low signal-to-noise ratio (SNR) that uses an end-to-end network (1D-Res...
Wind turbine rolling bearings are crucial components for ensuring the reliability and stability of wind power systems. Their failure can lead to significant economic losses and equipment downtime. Therefore, the accurate diagnosis of bearing faults i...
The accurate estimation of a 3D human pose is of great importance in many fields, such as human–computer interaction, motion recognition and automatic driving. In view of the difficulty of obtaining 3D ground truth labels for a dataset of 3D po...
Crack detection is essential for observing structural health and guaranteeing structural safety. The manual crack and other damage detection process is time-consuming and subject to surveyors’ biased judgments. The proposed Conv2D ResNet Expone...
Accurate evaluation of the Strouhal number is important for wind-resistant design, but traditional aerodynamic assessments are computationally expensive. To support rapid schematic design, this paper proposes a deep learning framework to predict the...
This paper reported a study on the 3-dimensional deep-learning-based automatic diagnosis of nasal fractures. (1) Background: The nasal bone is the most protuberant feature of the face; therefore, it is highly vulnerable to facial trauma and its fract...
Fritillaria thunbergii Miq. (ZBM) and Fritillaria hupehensis Hsiao et K.C. Hsia (HBBM) are two common medicinal and edible species of the genus Fritillaria, both possessing high economic and pharmacological value. Given their differences in pharmacol...
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