Results 31 to 40 of about 32,202 (267)
Object Segmentation in Images using EEG Signals [PDF]
, 2014 This paper explores the potential of brain-computer interfaces in segmenting objects from images. Our approach is centered around designing an effective method for displaying the image parts to the users such that they generate measurable brain reactions.
Bell C. J. +6 more
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Binarized Encoder-Decoder Network and Binarized Deconvolution Engine for Semantic Segmentation [PDF]
IEEE Access, 2021 Recently, semantic segmentation based on deep neural network (DNN) has attracted attention as it exhibits high accuracy, and many studies have been conducted on this. However, DNN-based segmentation studies focused mainly on improving accuracy, thus greatly increasing the computational demand and memory footprint of the segmentation network.
Hyunwoo Kim +4 more
openaire +2 more sources
Enhancement of Image Resolution by Binarization
, 2011 Image segmentation is one of the principal approaches of image processing. The choice of the most appropriate Binarization algorithm for each case proved to be a very interesting procedure itself.
Kanrar, Soumen, Mukherjee, Aroop
core +1 more source
MathematicsChaotic maps are sources of randomness formed by a set of rules and chaotic variables. They have been incorporated into metaheuristics because they improve the balance of exploration and exploitation, and with this, they allow one to obtain better ...
Felipe Cisternas-Caneo +5 more
doaj +1 more source
Automatic Document Image Binarization using Bayesian Optimization
, 2017 Document image binarization is often a challenging task due to various forms of degradation. Although there exist several binarization techniques in literature, the binarized image is typically sensitive to control parameter settings of the employed ...
Badekas E +9 more
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Multivariate Techniques for Identifying Diffractive Interactions at the LHC [PDF]
, 2009 31 pages, 14 figures, 11 tablesClose to one half of the LHC events are expected to be due to elastic or inelastic diffractive scattering. Still, predictions based on extrapolations of experimental data at lower energies differ by large factors in ...
Kuusela, Mikael +4 more
core +2 more sources
Finding Statistically Significant Interactions between Continuous Features
, 2019 The search for higher-order feature interactions that are statistically significantly associated with a class variable is of high relevance in fields such as Genetics or Healthcare, but the combinatorial explosion of the candidate space makes this ...
Borgwardt, Karsten, Sugiyama, Mahito
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Bimodal-Distributed Binarized Neural Networks
Mathematics, 2022 Binary neural networks (BNNs) are an extremely promising method for reducing deep neural networks’ complexity and power consumption significantly. Binarization techniques, however, suffer from ineligible performance degradation compared to their full-precision counterparts.
Tal Rozen +4 more
openaire +3 more sources
Computationally Efficient Implementation of Convolution-based Locally Adaptive Binarization Techniques [PDF]
, 2012 One of the most important steps of document image processing is binarization. The computational requirements of locally adaptive binarization techniques make them unsuitable for devices with limited computing facilities.
A.S. Abutaleb +15 more
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St. Petersburg Polytechnical University Journal: Physics and Mathematics, 2020 In the paper, the influence of phase distribution over the objects’ space on resolution and depth of field of computer-generated holograms has been investigated.
Koreshev Sergey +3 more
doaj +1 more source