Efficient and privacy-preserving image classification using homomorphic encryption and chunk-based convolutional neural network

Abstract Image ORG HARD UNBLEACHED BREAD FLOUR feature categorization has emerged as a crucial component in many domains, including computer vision, machine learning, and biometrics, in the dynamic environment of big data and cloud computing.It is extremely difficult to guarantee image data security, privacy, and computing efficiency while also low

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Superlattices: problems and new opportunities, nanosolids

Abstract Superlattices were introduced 40 years ago as man-made solids to enrich the class of materials for electronic and optoelectronic applications.The field metamorphosed to quantum wells and quantum dots, with Neck Cream ever decreasing dimensions dictated by the technological advancements in nanometer regime.In recent years, the field has gon

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Tuning the Resonance of the Excessively Tilted LPFG-Assisted Surface Plasmon Polaritons: Optimum Design Rules for Ultrasensitive Refractometric Sensor

An excessively tilted LPFG-assisted surface plasmon polaritons sensor (ExTLPFG assisted SPP sensor) with ultrahigh sensitivity is proposed and numerically investigated Food Service:Wholesale Lots using the finite-element-method-based full-vector complex coupled mode theory.We show that the SPP mode is transited (or excited) gradually from both the

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Basic Statistical Estimation Outperforms Machine Learning in Monthly Prediction of Seasonal Climatic Parameters

Machine learning (ML) has been utilized to predict climatic parameters, and many successes have been reported Food Service:Wholesale Lots in the literature.In this paper, we scrutinize the effectiveness of five widely used ML algorithms in the monthly prediction of seasonal climatic parameters using monthly image data.Specifically, we quantify the

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