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Abstract Background To evaluate binary classifications and their confusion matrices, scientific researchers can employ several statistical rates, accordingly to the goal of the experiment they are investigating. Despite ...

Presents a theoretically very simple, yet efficient, multiresolution approach to gray-scale and rotation invariant texture classification based on local binary patterns and nonparametric discrimination of sample and prot...

ObjectiveTo develop an accurate and efficient binary classification model for predicting the binding capacity of endocrine-disrupting chemicals （EDCs） to the G protein-coupled estrogen receptor （GPER）.MethodsGPER...

A brain computer interface (BCI) is a system which provides direct communication between the mind of a person and the outside world by using only brain activity (EEG). The event-related potential (ERP)-based BCI problem ...

ABSTRACT Intelligent and adaptive defence systems that can quickly thwart changing cyberthreats are becoming more and more necessary in the dynamic and data‐intensive Internet of things (IoT) environment. Using the NSL...

In this work, a structured hierarchy of hyperdatasets for Monkeypox image classification is presented, aiming to evaluate the robustness and generalization ability of deep classification models for Mpox detection. A syst...

The rapid advancement of generative artificial intelligence (AI) has obscured the distinction between human- and machine-created art, posing significant challenges to authentication, copyright, and artistic integrity. Th...

O presente artigo analisa, inicialmente, a posição majoritária da doutrina segundo a qual o Direito se constitui em autêntica e genuína ciência autônoma, abordando o conceito de ciência, a classificação binári...

The P300 component of event-related potentials (ERPs) is widely used in the implementation of brain computer interfaces (BCI). In this context, one of the main issues to solve is the binary classification problem that en...

Abstract Early and reliable smoke detection is critical for preventing fire-related disasters, safeguarding human lives, and ensuring infrastructure safety. Conventional sensor-based systems, however, are often constrain...

Abstract Canine gait analysis using wearable inertial sensors is gaining attention in veterinary clinical settings, as it provides valuable insights into a range of mobility impairments. Neurological and orthopedic condi...

Abstract National‐scale benthic marine habitat maps underpin monitoring and conservation of vulnerable marine and coastal ecosystems. Cloud‐based satellite remote sensing can streamline these processes over spatial s...

Abstract Machine-generated music (MGM) has become a groundbreaking innovation with wide-ranging applications, such as music therapy, personalised editing, and creative inspiration within the music industry. However, the ...

Abstract Background Holter electrocardiographic monitoring is a cornerstone of diagnostic testing for arrhythmogenic cardiomyopathy (ACM) in Boxer dogs, but physical activity during monitoring is not controlled. In human...

To address the challenges of aviation safety information overload in Pre-flight Information Bulletin (PIB) systems, this study proposes an intelligent classification framework (ERNIE-DPCNN) that integrates knowledge-enha...

Abstract BackgroundDepression affects more than 300 million people worldwide and is a leading contributor to the global disease burden. Traditional diagnostic methods, such as structured clinical interviews, ...

Kun-Yin Qiu,1,2,* Xiong-Yu Liao,1,2,* Hai-Lei Chen,2,3,* Hong Zheng,1,2,* Jian-Pei Fang,1,2 Dun-Hua Zhou1,2 1Department of Hematology/Oncology, Children’s Medical Center, Sun Yat-sen Mem...

Abstract Background Machine learning methods are widely used to detect behavioural data patterns. Although these new mathematical methods are useful tools, the interpretation of the results are often ambivalent unless ...

People are increasingly reliant on the internet for communication and various devices in their daily lives. The Internet of Things (IoT) has dramatically changed many industries by allowing more automation and easy data ...

Automatic music transcription, which is primarily the conversion of sound into a symbolic representation such as sheet music, is one of the major tasks in the field of music and computers. One of these tasks, automatic d...

Antimicrobial resistance represents a major global health challenge, particularly in the context of multidrug-resistant bacteria. Although conventional antibiotics and antimicrobial peptides (AMPs) both exert selective p...

Due to the simplicity of their implementations, least square support vector machine (LS-SVM) and proximal support vector machine (PSVM) have been widely used in binary classification applications. The conventional LS-SVM...

Document classification has already been widely studied. In fact, some studies compared feature selection techniques or feature space transformation whereas some others compared the performance of different algorithms. R...