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Accurate estimation of signal-to-noise ratio (SNR) in Scanning Electron Microscopy (SEM) is crucial because it evaluates the image quality. SEM images faced a challenge whereby Gaussian noise commonly appears in the imag...

Tuberculosis (TB) continues to be one of the foremost public health issues in the world, and remains the second most salient communicable cause of death after COVID-19. In 2022, TB accounted for 10.6 million new infectio...

The rapid growth and increasing complexity of Internet of Things (IoT) networks require efficient real-time monitoring and anomaly detection mechanisms. Traditional machine learning approaches often struggle to handle th...

For the structural health monitoring of composite materials, data analysis technology must be very sophisticated, capable of detecting fault patterns that are multi-level and complicated. A comprehensive deep learning pa...

This article applies deep learning-accelerated inverse design algorithms and discovers a spectrum of photonic power dividers with exceptional performance metrics despite the simplicity in the design geometry. The deep le...

Abstract Accurate prediction of bio-oil yield from pyrolysis of organic solid waste is still the main problem in the field of biomass valorization, mostly because of high variability in the composition and the heterogene...

Optical tweezers exploit light–matter interactions to trap particles ranging from single atoms to micrometer-sized eukaryotic cells. For this reason, optical tweezers are a ubiquitous tool in physics, biology, and nano...

The deep-learning revolution is providing enticing new opportunities to manipulate and harness light at all scales. By building models of light–matter interactions from large experimental or simulated datasets, deep le...

Objective: The prevalence of adjacent segment disease (ASD) following lumbar surgery is strongly linked to posterior lumbar interbody fusion (PLIF). The goal of this study was to create and validate a composite deep lear...

Abstract Seed selection constitutes the initial and one of the most critical steps in agricultural productivity. The identification of high-quality seeds is a labor-intensive and costly process that requires considerable...

Fluorescence imaging through the second near-infrared window (NIR-II,1000–1700 nm) allows in-depth imaging. However, current imaging systems use wide-field illumination and can only provide low-contrast 2D information,...

Abstract Recognizing tactical formations is a critical task in professional football performance analytics. However, existing methods often fail to capture the dynamic and continuously evolving nature of modern tactical ...

The selective broadband absorption of solar radiation plays a crucial role in applying solar energy. However, despite being a decade-old technology, the rapid and precise designs of selective absorbers spanning from the ...

Deep learning has become the dominant approach in artificial intelligence to solve complex data-driven problems. Originally applied almost exclusively in computer-science areas such as image analysis and nature language ...

We propose a metasurface antenna capable of real-time holographic beam steering. An array of reconfigurable dipoles can generate on-demand far-field patterns of radiation through the specific encoding of meta-atomic stat...

Optical cryptanalysis is essential to the further investigation of more secure optical cryptosystems. Learning-based attack of optical encryption eliminates the need for the retrieval of random phase keys of optical encr...

To address the critical limitations of conventional band-switching technologies – such as their slow speed, high energy consumption, and mechanical instability – this research introduces a novel deep-learning-driven ...

Abstract Intertidal macrobenthos are vital bioindicators of coastal ecosystem health due to their ecological roles, limited mobility, and sensitivity to environmental disturbances. However, traditional field‐based moni...

Abstract The rising complexity of urban areas, along with growing public safety needs, has made intelligent video surveillance systems more essential. The current surveillance systems that rely on human observation and p...

Abstract Objectives To develop and evaluate a deep learning model for diagnosing untreated rheumatoid arthritis (RA) using digital camera images of bilateral dorsal hands, benchmarking its performance against the widely-...

Abstract The integration of the sixth-generation (6G) communication technology and the Industrial Internet of Things (IIoT) has realized the intelligence and automation of industrial applications. However, due to the com...

Ulva prolifera (U. prolifera) green tides have become a recurring ecological issue in the Yellow Sea, posing serious threats to coastal ecosystems and regional economies. Traditional optical satellite index-threshold met...

Nanophotonic devices manipulate light at sub-wavelength scales, enabling tasks such as light concentration, routing, and filtering. Designing these devices to achieve precise light–matter interactions using structural ...

This work presents a hybrid deep learning approach for identifying students who are likely to experience academic difficulties in virtual learning environments. The proposed framework is evaluated on the Open University ...