Results 71 to 80 of about 214,409 (272)
A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data
Advanced Engineering Materials, EarlyView.Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour +5 more
wiley +1 more source
Efficient sparse coding in early sensory processing: lessons from signal recovery. [PDF]
PLoS Computational Biology, 2012 Sensory representations are not only sparse, but often overcomplete: coding units significantly outnumber the input units. For models of neural coding this overcompleteness poses a computational challenge for shaping the signal processing channels as ...
András Lörincz +2 more
doaj +1 more source
A fast approach for overcomplete sparse decomposition based on smoothed L0 norm
, 2008 In this paper, a fast algorithm for overcomplete sparse decomposition, called SL0, is proposed. The algorithm is essentially a method for obtaining sparse solutions of underdetermined systems of linear equations, and its applications include ...
Babaie-Zadeh, Massoud +2 more
core +7 more sources
Transformational Sparse Coding
, 2017 A fundamental problem faced by object recognition systems is that objects and their features can appear in different locations, scales and orientations. Current deep learning methods attempt to achieve invariance to local translations via pooling, discarding the locations of features in the process.
Gklezakos, Dimitrios C. +1 more
openaire +2 more sources
Advanced Functional Materials, EarlyView.This study uncovers the unexplored role of intermolecular interactions in multiphoton absorption in coordination polymers. By analyzing [Zn2tpda(DMA)2(DMF)0.3], it shows how the electronic coupling of the chromophores and confinement in the MOF enhance two‐and three‐photon absorption.
Simon Nicolas Deger +11 more
wiley +1 more source
Integrated Sparse Coding With Graph Learning for Robust Data Representation
IEEE Access, 2020 Sparse coding is a popular technique for achieving compact data representation and has been used in many applications. However, the instability issue often causes degeneration in practice and thus attracts a lot of studies.
Yupei Zhang, Shuhui Liu
doaj +1 more source
Predicting Atomic Charges in MOFs by Topological Charge Equilibration
Advanced Functional Materials, EarlyView.An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi +2 more
wiley +1 more source
Imaging of Biphoton States: Fundamentals and Applications
Advanced Functional Materials, EarlyView.Quantum states of two photons exhibit a rich polarization and spatial structure, which provides a fundamental resource of strongly correlated and entangled states. This review analyzes the physics of these intriguing properties and explores the various techniques and technologies available to measure them, including the state of the art of their ...
Alessio D'Errico, Ebrahim Karimi
wiley +1 more source
LOW-DIMENSIONAL STRUCTURES: SPARSE CODING FOR NEURONAL ACTIVITY [PDF]
Journal of Innovative Optical Health Sciences, 2013 Neuronal ensemble activity codes working memory. In this work, we developed a neuronal ensemble sparse coding method, which can effectively reduce the dimension of the neuronal activity and express neural coding.
YUNHUA XU, WENWEN BAI, XIN TIAN
doaj +1 more source
Variational Sparse Coding [PDF]
, 2019 Unsupervised discovery of interpretable features and controllable generation with highdimensional data are currently major challenges in machine learning, with applications\ud in data visualisation, clustering and artificial\ud data synthesis. We propose a model based\ud on variational auto-encoders (VAEs) in which\ud interpretation is induced through ...
Tonolini, Francesco +2 more
openaire