Results 81 to 90 of about 31,786 (276)
Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang +4 more
wiley +1 more source
IPv6 over Low Power Wireless Personal Area Networks (6LoWPANs), in the next generation of wireless sensor networks, represent an emerging field which can be integrated with Internet technology.
Mohamed Kasraoui +2 more
doaj +1 more source
This review aims to provide a broad understanding for interdisciplinary researchers in engineering and clinical applications. It addresses the development and control of magnetic actuation systems (MASs) in clinical surgeries and their revolutionary effects in multiple clinical applications.
Yingxin Huo +3 more
wiley +1 more source
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee +7 more
wiley +1 more source
Restricted Tweedie stochastic block models
Abstract The stochastic block model (SBM) is a widely used framework for community detection in networks, where the network structure is typically represented by an adjacency matrix. However, conventional SBMs are not directly applicable to an adjacency matrix that consists of nonnegative zero‐inflated continuous edge weights.
Jie Jian, Mu Zhu, Peijun Sang
wiley +1 more source
Rank‐based estimation of propensity score weights via subclassification
Abstract Propensity score (PS) weighting estimators are widely used for causal effect estimation and enjoy desirable theoretical properties, such as consistency and potential efficiency under correct model specification. However, their performance can degrade in practice due to sensitivity to PS model misspecification.
Linbo Wang +3 more
wiley +1 more source
Almost Difference Set Pairs and Ideal Three-Level Correlation Binary Sequence Pairs
Almost difference set pairs are used in cryptography and coding theory, and a majority of the acknowledged almost difference set pairs are constructed by Chinese remainder theorem, cyclotomy or interleaving.
Wei Zhao, Yue Wu, Yaya Zhang, Yanguo Jia
doaj +1 more source
This work explores the conversion from residues to binary representation in RNS using the Chinese remainder theorem (CRT) or mixed radix conversion (MRC) algorithms. The proposed approach relocates CRT multiplicative inverses to the arithmetic stage without extra cost, improving scalability while achieving speedups over state‐of‐the‐art MRC ...
Gabriel B. M. Fernandes +2 more
wiley +1 more source
Around the Chinese Remainder Theorem
We prove an explicit Chinese Remainder Theorem for one variable polynomials with complex coefficients, and derive some consequences.
Didry, Jean-Marie, Gaillard, Pierre-Yves
openaire +2 more sources
ABSTRACT The properties of plasmas in the low‐density limit are described by virial expansions. Analytical expressions are known for the lowest virial coefficients from Green's function approaches. Recently, accurate path‐integral Monte Carlo (PIMC) simulations were performed for the hydrogen plasma at low densities by Filinov and Bonitz (Phys. Rev.
Gerd Röpke +3 more
wiley +1 more source

