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Spiking neural networks (SNNs) offer a biologically inspired, energy-efficient alternative to conventional artificial neural networks (ANNs). However, deep SNNs struggle to process complex EEG signals because their spike...

Holograms which reconstruct the transverse profile of light with complex-amplitude information have demonstrated more excellent performances with an improved signal-to-noise ratio compared with those containing amplitude...

Thermoelectric generators offer a promising solution for sustainable, low-maintenance energy harvesting in smart agriculture, especially for powering off-grid sensor nodes and microgrid systems. However, their inherently...

In response to the unstable accuracy rate of fault location in distribution network lines and the significant impact of communication with distribution automation devices, the fault perception analysis of distribution ne...

IntroductionReliable classification of lung nodules from computed tomography (CT) images remains a challenging problem due to variations in image intensity, noise, and unstable feature representations during deep network...

Accurate velocity estimation plays a key role in ensuring precise motion control and safe navigation of ground robots. Ground-view event cameras provide a reliable sensing modality for this task. They exploit the static ...

Abstract Along with the development and growth of the internet network, there is an increasing needed to use protection systems such as intrusion classification and detection systems that protect computer and network fro...

Abstract In the realm of engineering practice, various factors such as limited availability of measurement data and complex working conditions pose significant challenges to obtaining accurate load spectra. Thus, accurat...

BackgroundThe thermal diffusivity and vertical seepage velocity of porous media are critical to characterizing the mechanisms underlying subsurface heat transfer. These two parameters are typically determined through inv...

The long wavelength infrared (LWIR) range (8–14 µm) is crucial for thermal radiation detection, necessitating effective camouflage against advanced infrared technologies. Conventional camouflage approaches often rel...

ABSTRACT The growing use of neural networks in privacy‐sensitive applications necessitates architectures that inherently protect both data and model integrity. We present a model‐inversion‐resistant physical unclon...

BackgroundRecently, plant disease detection and classification have become major concerns in agriculture. Early detection of plant diseases supports farmers to take precautionary actions to prevent the spread of infectio...

Abstract The study of multi classification of data has become one of the important issues which geographical studies focus on especially those which take their data from satellites. Two ways of classification has been ta...

Optimization of design parameters based on electromagnetic simulation of microwave circuits is a timeconsuming and iterative procedure. To provide a fast and accurate frequency response for a given case study, this paper...

Biotic and abiotic stresses reduce crop yields, yet existing image‑based diagnostic models are often crop‑specific, computationally intensive, and poorly interpretable. This study present: (i) a multi-crop diagnostic...

The search for new energy sources has intensified today worldwide. In Argentina, bioenergy continues to be the energy with minor participation in the energy matrix. Therefore, research should focus on searching for new s...

In recent years, convolutional neural networks and deep neural networks have been used extensively in various fields of analytical chemistry. The use of these models for calibration tasks has been highly effective; howev...

Abstract This study uses the Levenberg–Marquardt strategy with feed forward neural networks (LMS-FNN) to inspect the Soret-Dufour effect on radiative hybrid nanofluid flow across a Riga plate with gyrotactic microorgan...

Reliable estimation of reference evapotranspiration (ET0) is essential for irrigation scheduling and agricultural water-resources management. Although the FAO-56 Penman–Monteith equation is widely accepted as the stand...

In this research, we address a critical problem for strawberry growers in Lima: the management of phytosanitary diseases. Traditionally, these farmers relied on time-consuming, imprecise, and error-prone visual observati...

As a non-destructive and rapid technique, optical scatterometry has gained widespread use in the measurement of film thickness and optical constants. The recent advances in deep learning have presented new and powerful a...

Abstract Background Chronic kidney disease (CKD) frequently causes death in older cats; its early detection is challenging. Objectives To build a sensitive and specific model for early prediction of CKD in cats using art...

Abstract The last decade witnessed a great evolution on the fields of computer science, artificial intelligence, communication and data transmission. This evolution draw the attention of specialists to design a modern cr...

Abstract Background Collagenous colitis (CC) is diagnosed histologically and is characterised by a thickened subepithelial collagen band together with inflammatory and epithelial changes. Although routine haematoxylin an...