Sarcoidosis is a chronic, idiopathic, multisystemic inflammatory disease characterized by non-caseating granulomas, most commonly affecting the lungs and mediastinal lymph nodes. Radiological imaging plays a fundamental role in the diagnosis, assessm...
The purpose of multi-modal visual information fusion is to integrate the data of multi-sensors to generate an image with higher quality, more information, and greater clarity so that it contains more complementary information and fewer redundant feat...
This work presents the “First-Order Features Adjoint Sensitivity Analysis Methodology for Neural Integro-Differential Equations of Fredholm-Type” (1st-FASAM-NIDE-F) and the “Second-Order Features Adjoint Sensitivity Analysis Methodo...
This work introduces the mathematical framework of the novel “First-Order Features Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations” (1st-FASAM-NODE). The 1st-FASAM-NODE methodology produces and computes...
This work illustrates the application of the “First-Order Features Adjoint Sensitivity Analysis Methodology for Neural Integro-Differential Equations of Fredholm-Type” (1st-FASAM-NIDE-F) and the “Second-Order Features Adjoint Sensit...
This work presents the mathematical frameworks of the “First-Order Features Adjoint Sensitivity Analysis Methodology for Neural Integro-Differential Equations of Volterra-Type” (1st-FASAM-NIDE-V) and the “Second-Order Features Adjoi...
This work presents an illustrative application of the newly developed “Second-Order Features Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations (2nd-FASAM-NODE)” methodology to determine most efficiently t...
Feature selection is a typical multiobjective problem including two conflicting objectives. In classification, feature selection aims to improve or maintain classification accuracy while reducing the number of selected features. In practical applicat...
Symmetry plays a critical role in preserving the structural balance and statistical integrity of datasets, particularly in privacy-preserving machine learning. Differential privacy introduces random noise to individual data points to ensure privacy w...
To extract effective features for the terrain classification of hyperspectral remote-sensing images (HRSIs), a spectral fractional-differentiation (SFD) feature of HRSIs is presented, and a criterion for selecting the fractional-differentiation order...
Feature selection can effectively remove redundant and irrelevant features in classification tasks; however, feature subset search on datasets with different dimensionalities still faces challenges such as strong initialization randomness, complex se...
Feature extraction of electroencephalography (EEG) signals plays a significant role in the wearable computing field. Due to the practical applications of EEG emotion calculation, researchers often use edge calculation to reduce data transmission time...
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...
The selection of critical features from microarray data as biomarkers holds significant importance in disease diagnosis and drug development. It is essential to reduce the number of biomarkers while maintaining their performance to effectively minimi...
Optimization algorithms play a crucial role in solving complex problems across various fields, including global optimization and feature selection (FS). This paper presents the enhanced polar lights optimization with cryptobiosis and differential evo...
In machine learning, feature selection is a fundamental component that plays a crucial role in improving prediction accuracy and reducing the computational time of classification models. Feature selection involves eliminating irrelevant or redundant...
We propose a method for selecting the optimal set of weather features for wind energy prediction. This problem is tackled by developing a wrapper approach that employs binary differential evolution to search for the best feature subset, and an ensemb...
Background and Objectives: This study aimed to identify and analyze imaging and pathological features that differentiate liver metastases from primary liver cancer in patients with histopathological confirmation, and to evaluate the diagnostic accura...
Transparent curved surfaces of glass packaging bottles produce structural responses that can obscure local appearance asymmetries associated with defects, complicating their segmentation across different scales and shapes. To address these challenges...
Super-resolution reconstruction of remote sensing images has significant application value in fields such as smart cities, land monitoring, and traffic management. However, current super-resolution methods often overlook the differences between seman...
Accurate lesion segmentation in ultrasound images remains challenging because of severe speckle noise, low tissue contrast, ambiguous boundaries, and substantial variations in lesion morphology and scale. To address these limitations, we propose RDPA...
Feature selection is a preprocessing step in machine learning that aims to reduce dimensionality and improve performance. The approaches for feature selection are often classified according to the evaluation of a subset of features as filter, wrapper...
Change detection (CD) of natural land cover is important for environmental protection and to maintain an ecological balance. The Landsat series of satellites provide continuous observation of the Earth’s surface and is sensitive to reflection o...
The automatic identification of emotions from speech holds significance in facilitating interactions between humans and machines. To improve the recognition accuracy of speech emotion, we extract mel-frequency cepstral coefficients (MFCCs) and pitch...
Multi-objective feature selection provides an effective framework for high-dimensional data analysis by jointly considering classification performance and feature subset size. However, redundant and irrelevant features may degrade the quality of the...
With the growing prevalence of cybercrime, botnets have emerged as a significant threat, infiltrating an increasing number of legitimate computers annually. Challenges arising for organizations, educational institutions, and individuals as a result o...
To date, the usage of electromyography (EMG) signals in myoelectric prosthetics allows patients to recover functional rehabilitation of their upper limbs. However, the increment in the number of EMG features has been shown to have a great impact on p...
Cognitive dysfunction is a frequent complication of type 2 diabetes mellitus (T2DM), usually accompanied by metabolic disorders. However, the metabolic changes in diabetic cognitive dysfunction (DCD) patients, especially compared to T2DM groups, are...
Transformer architectures, originally developed for language modeling, have been increasingly applied to time-series forecasting, but deploying them on sensitive data such as patient vital signs, financial records, or energy use raises privacy risks...
Paramyxovirus (PMV) entry requires the coordinated action of two envelope glycoproteins, the receptor binding protein (RBP) and fusion protein (F). The sequence of events that occurs during the PMV entry process is tightly regulated. This regulation...
Background: In recent years, microarray datasets have been used to store information about human genes and methods used to express the genes in order to successfully diagnose cancer disease in the early stages. However, most of the microarray dataset...
Quantifying the temporal and spatial patterns of impervious surfaces (IS) is important for assessing the environmental and ecological impacts of urbanization. In order to better extract IS, and to explore the divergence in urbanization in different r...
The critical analysis of the new experimental data obtained by the ATLAS Collaboration group at 13 TeV is presented and the problem of the tension between data of the ATLAS and TOTEM Collaborations is considered. The analysis of new effects discovere...
The term “acne-like eruptions” encompasses a variety of skin conditions resembling acne vulgaris. While both acne-like dermatoses and true acne are frequently observed in clinical settings, differentiating between the two might be challen...
Despite the achievements of modern medicine, tuberculosis remains one of the leading causes of mortality globally. The difficulties in differential diagnosis have particular relevance in the case of suspicion of tuberculosis with other granulomatous...
Among cardiomyopathies, the hypertrophic phenotype is the most common, and hypertrophic cardiomyopathy (HCM) phenocopies represent a heterogeneous group of conditions. They are defined by a left ventricular wall thickness ≥15 mm in the absence of...
Differentially private stochastic gradient descent (DP-SGD) enables neural network training with formal privacy guarantees, but its utility depends on model architecture, data modality, and privacy budget. DP-RVFL freezes random hidden features and p...
Fast and accurate recognition of basic waveforms is important in embedded sensing, signal testing, and hardware measurement systems, especially under strict constraints on computation, memory, and power consumption. To address this problem, this pape...
To address misclassification and reduced accuracy in semantic change detection caused by class imbalance and variable object sizes, this paper improves BGSNet and proposes a new change detection network, SRDFNet (Semantic Refinement and Differential...
In this article, we propose that elements of heritage language grammars—both in the form of axiomatic features and larger combined representational units—are not easily lost over the course of the lifespan. This view contrasts with altern...
Burkitt lymphoma (BL) is an aggressive mature B-cell lymphoma that represents one of the most studied human malignancies. Initially described in equatorial Africa by the Irish surgeon Denis P. Burkitt, African (endemic) Burkitt lymphoma was the first...
To improve the recognition accuracy of ship-radiated noise, a feature extraction method based on regenerated phase-shifted sinusoid-assisted empirical mode decomposition (RPSEMD), mutual information (MI), and differential symbolic entropy (DSE) is pr...
In large-capacity energy storage systems, instructions are decomposed typically using an equalized power distribution strategy, where clusters/modules operate at the same power and durations. When dispatching shifts from stable single conditions to i...
Background: Esophageal strictures lacking typical malignant endoscopic features present a significant diagnostic challenge, often mimicking malignancy on imaging while concealing their true nature under regular white-light endoscopy. This study evalu...
COVID-19 pneumonia represents a challenging health emergency, due to the disproportion between the high transmissibility, morbidity, and mortality of the virus and healthcare systems possibilities. Literature has mainly focused on COVID-19 pneumonia...
As an emerging artificial intelligence technology, federated learning plays a significant role in privacy preservation in machine learning, although its main objective is to prevent peers from peeping data. However, attackers from the outside can ste...
The purpose of this study is to introduce differential dose–volume histogram (dDVH) features into machine learning for radiation pneumonitis (RP) prediction and to demonstrate the predictive performance of the developed model based on integrate...
Image fusion is the generation of an informative image that contains complementary information from the original sensor images, such as texture details and attentional targets. Existing methods have designed a variety of feature extraction algorithms...
The high-accuracy detection of multiple distinct human emotions is crucial for advancing affective computing, mental health diagnostics, and human–computer interaction. The integration of deep learning networks with entropy measures holds signi...
Hepatic echinococcosis, caused by Echinococcus species, remains a significant global health concern, with cystic echinococcosis (CE) being widespread and alveolar echinococcosis (AE) representing a rarer but more aggressive form. CE generally demonst...
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