Results 101 to 110 of about 6,366,089 (278)
Advanced Functional Materials, EarlyView.The physical realization of artificial neurons is a critical challenge for energy‐efficient neuromorphic computing. This review presents a comprehensive analysis of the evolution of artificial neuron implementations from conventional CMOS to emerging post‐CMOS technologies.
Kannan Udaya Mohanan +4 more
wiley +1 more source
Alignment of vector fields on manifolds via contraction mappings
Учёные записки Казанского университета: Серия Физико-математические науки, 2018 According to the manifold hypothesis, high-dimensional data can be viewed and meaningfully represented as a lower-dimensional manifold embedded in a higher dimensional feature space. Manifold learning is a part of machine learning where an intrinsic data
O.N. Kachan +2 more
doaj
Sheaves of nonlinear generalized functions and manifold-valued distributions
, 2009 This paper is part of an ongoing program to develop a theory of generalized differential geometry. We consider the space G[X,Y] of Colombeau generalized functions defined on a manifold X and taking values in a manifold Y. This space is essential in order
Steinbauer, Roland +5 more
core +1 more source
Covalent Functionalization of 2D Semiconductors: A Roadmap to Advanced Electronic Devices
Advanced Functional Materials, EarlyView.This Review presents recent advances in the covalent functionalization strategies for two‐dimensional semiconductors and their implementation in modern technologies. Layered materials are modified through diverse molecular chemistries (e.g., thiols, diazonium salts, alkyl halides, and electron‐deficient species) to tailor their surface properties ...
Ramiro Quirós‐Ovies +2 more
wiley +1 more source
An Adaptive Inhibitory WSe2 Transistor for Retinomorphic In‐Sensor Image Processing
Advanced Functional Materials, EarlyView.Conventional retinomorphic devices typically require deliberate gate‐bias tuning for each illumination condition. In this paper, we demonstrate an adaptive inhibitory WSe2 transistor that uses photo‐induced regime shift between the subthreshold and accumulation modes to achieve decision‐free, intensity‐adaptive image processing within a single pixel ...
Juhwan Baek +12 more
wiley +1 more source
Improvement of Supervised Shape Retrieval by Learning the Manifold Space
International Journal of Information and Communication Technology Research, 2012 Manifold learning is the technique that aims for finding a constructive way to embed the data from a highdimensional space into a low-dimensional one based on non-linear approaches.
Mohammad Ali Zare Chahooki +1 more
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Advanced Functional Materials, EarlyView.Printed negative‐dielectric‐anisotropy liquid‐crystal droplets enable multidimensional full‐vectorial optical‐field sensing across polarization, phase, and wavelength, while also generating tunable skyrmionic‐like complex optical fields. ABSTRACT Adaptive manipulation of vectorial optical fields is important for optical metrology, imaging, and ...
Jinge Guo +14 more
wiley +1 more source
Manifold Mixup: Better Representations by Interpolating Hidden States [PDF]
, 2019 Deep neural networks excel at learning the training data, but often provide incorrect and confident predictions when evaluated on slightly different test examples. This includes distribution shifts, outliers, and adversarial examples.
Verma, Vikas +6 more
core +1 more source
Optical Detection of Cellular Signals at Material Interfaces
Advanced Healthcare Materials, EarlyView.Emerging functional materials are transforming optical detection of cellular signals. This review highlights optical techniques that exploit the unique optical properties of diverse materials to detect and quantify cellular electrical, chemical, and mechanical signals, and discusses key opportunities and challenges.
Xuchen Ren +5 more
wiley +1 more source
Incremental Unsupervised-Learning of Appearance Manifold with View-Dependent Covariance Matrix for Face Recognition from Video Sequences [PDF]
, 2009 We propose an appearance manifold with view-dependent covariance matrix for face recognition from video sequences in two learning frameworks: the supervised-learning and the incremental unsupervised-learning. The advantages of this method are, first, the
MURASE, Hiroshi +3 more
core