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...
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...
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.,...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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,...
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...
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...
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...
Almonds are a highly valued nut due to their rich protein and nutritional content. However, they are vulnerable to aflatoxin B1 (AFB1) contamination in warm and humid environments. Consumption of AFB1-contaminated almonds can pose serious health risk...
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...
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...
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...
To improve the feature extraction method for ship trajectories and enhance trajectory classification performance, this paper proposes a ship trajectory classification model that combines a one-dimensional residual network (ResNet1D) and an attention-...
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...
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...
Falls among the elderly are a significant public health issue, resulting in about 684,000 deaths annually. Such incidents often lead to severe consequences including fractures, contusions, and cranial injuries, immensely affecting the quality of life...
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...
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...
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...
Deep learning-based crop mapping from hyperspectral satellite data offers immense potential for capturing subtle phenological differences, yet leveraging sparse time series remains a major methodological challenge. This study evaluates the ability of...
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-...
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...
Aflatoxin B1, a toxic carcinogen frequently contaminating almonds, nuts, and food products, poses significant health risks. Therefore, a rapid and non-destructive detection method is crucial to detect aflatoxin B1-contaminated almonds to ensure food...
An accurate whole heart segmentation (WHS) on medical images, including computed tomography (CT) and magnetic resonance (MR) images, plays a crucial role in many clinical applications, such as cardiovascular disease diagnosis, pre-surgical planning,...
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...
Object recognition represents the ability of a system to identify objects, humans or animals in images. Within this domain, this work presents a comparative analysis among different classification methods aiming at Tactode tile recognition. The cover...
Reliable person segmentation with sparse 3D sensors degrades significantly under adverse atmospheric conditions. This work presents a controlled comparative evaluation of four segmentation architectures—U-Net, Mask R-CNN, DeepLabV3+, and FCN-Re...
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...
Machined surfaces are rough from a microscopic perspective no matter how finely they are finished. Surface roughness is an important factor to consider during production quality control. Using modern techniques, surface roughness measurements are ben...
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