Results 21 to 30 of about 163,100 (319)
Optimization of the 2P fifth degree convolution kernel in the spectral domain [PDF]
Bulletin of Natural Sciences Research, 2023 The first part of the paper describes a two-parameter (2P) fifth-order interpolation kernel, r. After that, from the 2P kernel, the kernel components were created.
Savić Nataša +2 more
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IET Computer Vision, 2021 Three‐dimensional (3D) shape reconstruction of objects requires multiple scans and complex reconstruction algorithms. An alternative approach is to infer the 3D shape of an object from a single depth image (i.e. single depth view).
Edwin Valarezo Añazco +2 more
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SIAM Journal on Optimization, 2019 The Moreau envelope is one of the key convexity-preserving functional operations in convex analysis, and it is central to the development and analysis of many approaches for convex optimization. This paper develops the theory for an analogous convolution operation, called the polar envelope, specialized to gauge functions.
Michael P. Friedlander +2 more
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Comb Convolution for Efficient Convolutional Architecture
CoRR, 2019 15 ...
Dandan Li +3 more
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An area-efficient 2-D convolution implementation on FPGA for space applications [PDF]
, 2011 The 2-D Convolution is an algorithm widely used in image and video processing. Although its computation is simple, its implementation requires a high computational power and an intensive use of memory.
Stefano Di Carlo +11 more
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Multipliers of Banach valued weighted function spaces
International Journal of Mathematics and Mathematical Sciences, 2000 We generalize Banach valued spaces to Banach valued weighted function spaces and study the multipliers space of these spaces. We also show the relationship between multipliers and tensor product of Banach valued weighted function spaces.
Serap Öztop
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Enhanced CNN for image denoising
CAAI Transactions on Intelligence Technology, 2019 Owing to the flexible architectures of deep convolutional neural networks (CNNs) are successfully used for image denoising. However, they suffer from the following drawbacks: (i) deep network architecture is very difficult to train.
Chunwei Tian +5 more
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Convolution Inference via Synchronization of a Coupled CMOS Oscillator Array
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, 2020 Oscillator neural networks (ONNs) are a promising hardware option for artificial intelligence. With an abundance of theoretical treatments of ONNs, few experimental implementations exist to date.
Dmitri E. Nikonov +8 more
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Certain Properties of Harmonic Functions Defined by a Second-Order Differential Inequality
Mathematics, 2023 The Theory of Complex Functions has been studied by many scientists and its application area has become a very wide subject. Harmonic functions play a crucial role in various fields of mathematics, physics, engineering, and other scientific disciplines ...
Daniel Breaz +4 more
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Fuzzy Sets and Systems, 2018 We propose two convolution operations on the set of functions between two bounded lattices and investigate the algebraic structure they constitute, in particular the lattice laws they satisfy. Each of these laws requires the restriction to a specific subset of functions, such as normal, idempotent or convex functions. Combining all individual results,
Miguel Turullols, Laura de +2 more
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