Results 81 to 90 of about 57,147 (259)
KSVD-Based Multiple Description Image Coding
IEEE Access, 2019 In this paper, we present a new multiple description coding scheme, which is based on a sparse dictionary training method called K singular value decomposition (KSVD).
Guina Sun +5 more
doaj +1 more source
Advanced Materials, EarlyView.Drawing inspiration from the layered hard‐soft architecture found in sea sponges, this work establishes a new framework for architected cementitious composites (ACC) through multi‐material additive manufacturing (MMAM) process. The integration of mortar and elastomer phases into layered architectures enables synergistic toughening mechanisms, including
Aimane Najmeddine +5 more
wiley +1 more source
Characterizing the sparseness of neural codes
Network: Computation in Neural Systems, 2001 It is often suggested that efficient neural codes for natural visual information should be 'sparse'. However, the term 'sparse' has been used in two different ways--firstly to describe codes in which few neurons are active at any time ('population sparseness'), and secondly to describe codes in which each neuron's lifetime response distribution has ...
Willmore, B, Tolhurst, D
openaire +2 more sources
Advanced Materials, EarlyView.The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source
An Accurate and Efficient Device-Free Localization Approach Based on Sparse Coding in Subspace
IEEE Access, 2018 In practical device-free localization (DFL) applications, for enlarging the monitoring area and improving localization accuracy, too many nodes need to be deployed, which results in a large volume of DFL data with high dimensions.
Huakun Huang +5 more
doaj +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
Advanced Materials, EarlyView.This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Switchable Magnonic Crystals Based on Spin Crossover/CrSBr Heterostructures
Advanced Materials, EarlyView.Multiscale modeling is employed to investigate the functionality of a light‐controlled, tunable magnonic crystal based on spin‐crossover Fe‐pz molecules integrated with a monolayer of CrSBr. Ab initio simulations confirm that the molecules remain functional on the CrSBr surface, while a semiclassical elastic model demonstrates that light‐induced ...
Andrei Shumilin +4 more
wiley +1 more source
Mechanistically Interpretable Artificial Intelligence for Designing Oxygen Electrocatalysts
Advanced Materials, EarlyView.Mechanistically interpretable artificial intelligence screens nearly seven million perovskite compositions and identifies key descriptors—d‐p hybridization and densification resistance—that govern oxygen electrocatalysis. The discovered BaCo0.8Nb0.1Zr0.1O3‐δ achieves a record 2.68 W cm−2 peak power density at 600°C with over 500 h of durable operation ...
Xueyu Hu +15 more
wiley +1 more source
Advanced Materials, EarlyView.Coupled materials design enables a monolithic fiber that integrates complementary sensing regimes into a single wearable strand. By preserving informative signal features across subtle physiological deformation, large body motion, and mixed mechanical inputs, the dual‐gradient architecture generates synchronized, less redundant outputs that improve ...
Yunheum Lee +13 more
wiley +1 more source