Results 71 to 80 of about 965,256 (248)

Emergence of a Hexagonal Fe2S2 Single Layer Without a Bulk Counterpart via Phase Transformation

open access: yesAdvanced Functional Materials, EarlyView.
Upon annealing, single‐layer Mackinawite iron sulfide transforms into a previously unknown hexagonal Fe2S2${\rm Fe}_2{\rm S}_2$ phase with β$\beta$‐CuI structure. STM, LEED, and first‐principles calculations identify the structure and show that electronic correlations and magnetic order are important for its stability.
Affan Safeer   +10 more
wiley   +1 more source

Facial Expression Recognition via Non-Negative Least-Squares Sparse Coding

open access: yesInformation, 2014
Sparse coding is an active research subject in signal processing, computer vision, and pattern recognition. A novel method of facial expression recognition via non-negative least squares (NNLS) sparse coding is presented in this paper.
Ying Chen, Shiqing Zhang, Xiaoming Zhao
doaj   +1 more source

Dictionary-based sparse coding.

open access: yes, 2018
Dictionary-based sparse coding.
Tabassam Nawaz (4984502)   +4 more
core   +1 more source

An Antimicrobial, Cell‐Adhesive, and Growth Factor‐Producing Living Material Engineered From Bacillus subtilis Biofilms for Wound Healing

open access: yesAdvanced Healthcare Materials, EarlyView.
Bacillus subtilis is engineered to produce cell‐adhesive biofilms by functionalization of its biofilm scaffold protein TasA with a cell‐adhesion sequence. Living bacteria within the biofilm are also engineered to secrete growth factors and natively produce antimicrobial peptides (AMPs), resulting in a cell‐adhesive, antimicrobial, and growth factor ...
Mélanie Côté‐Cyr   +3 more
wiley   +1 more source

Detection of Pitting in Gears Using a Deep Sparse Autoencoder

open access: yesApplied Sciences, 2017
In this paper; a new method for gear pitting fault detection is presented. The presented method is developed based on a deep sparse autoencoder. The method integrates dictionary learning in sparse coding into a stacked autoencoder network.
Yongzhi Qu   +3 more
doaj   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

open access: yesAdvanced 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

Are v1 simple cells optimized for visual occlusions? : A comparative study [PDF]

open access: yes, 2013
: Simple cells in primary visual cortex were famously found to respond to low-level image components such as edges. Sparse coding and independent component analysis (ICA) emerged as the standard computational models for simple cell coding because they ...
Lücke, Jörg   +11 more
core   +2 more sources

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

open access: yesAdvanced 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

Multi-targets device-free localization based on sparse coding in smart city

open access: yesInternational Journal of Distributed Sensor Networks, 2019
With the continuous expansion of the market of device-free localization in smart cities, the requirements of device-free localization technology are becoming higher and higher.
Min Zhao   +3 more
doaj   +1 more source

Descriptors to Dynamics: A Materials and Device Perspective on in‐Materio Physical Reservoir Computing for Neuromorphic Edge Intelligence

open access: yesAdvanced Materials, EarlyView.
Intrinsic material dynamics are harnessed as computational resources for neuromorphic in‐materio physical reservoir computing. Defects, ionic motion, interfaces, percolation, geometry, and biasing shape transient states that provide fading memory, nonlinearity, and high‐dimensional projection for simple readout. A descriptor‐to‐dynamics framework links
Kshitij RB Singh   +5 more
wiley   +1 more source

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