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Digital Computation of Linear Canonical Transforms
TLDR
In this paper, two algorithms for the computation of linear canonical transforms (LCTs) from the samples of the input signal in time are discussed. Expand
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Fast and accurate computation of two-dimensional non-separable quadratic-phase integrals.
TLDR
We report a fast and accurate algorithm for numerical computation of two-dimensional non-separable linear canonical transforms (2D-NS-LCTs). Expand
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Semantic Structure and Interpretability of Word Embeddings
TLDR
Dense word embeddings are substantially successful in capturing semantic relations among words, so a meaningful semantic structure must be present in the respective vector spaces. Expand
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MARVEL: A Large-Scale Image Dataset for Maritime Vessels
TLDR
We introduce a large-scale image dataset for maritime vessels, consisting of 2 million user uploaded images and their attributes including vessel identity, type, photograph category and year of built, collected from a community website. Expand
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Efficient computation of quadratic-phase integrals in optics.
We present a fast NlogN time algorithm for computing quadratic-phase integrals. This three-parameter class of integrals models propagation in free space in the Fresnel approximation, passage throughExpand
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Deep Iterative Reconstruction for Phase Retrieval
TLDR
We develop a phase retrieval algorithm that utilizes two DNNs together with the model-based HIO method to improve the reconstructions. Expand
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Quadruplet Selection Methods for Deep Embedding Learning
TLDR
We focus on deep embedding learning by using a multi-task learning framework in which the hierarchical labels (coarse and fine labels) of the samples are utilized both for classification and a quadruplet-based loss function. Expand
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Fast and accurate algorithm for the computation of complex linear canonical transforms.
TLDR
A fast and accurate algorithm is developed for the numerical computation of the family of complex linear canonical transforms (CLCTs), which represent the input-output relationship of complex quadratic-phase systems. Expand
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Evaluation of Feature Channels for Correlation-Filter-Based Visual Object Tracking in Infrared Spectrum
TLDR
We assess the performance of two state-of-the-art correlationfilter-based object tracking methods on Linköping Thermal InfraRed (LTIR) dataset of medium wave and longwave infrared videos, using deep convolutional neural networks (CNN) features as well as other traditional hand-crafted descriptors. Expand
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Sparse representation of two- and three-dimensional images with fractional Fourier, Hartley, linear canonical, and Haar wavelet transforms
TLDR
Fractional Fourier Transform are introduced as sparsifying transforms.Linear Canonical Transforms are Introduced as Sparsifying Transforms.Hartley and simplified fractional Hartley transforms, which differ from corresponding Fourier transforms in that they produce real outputs for real inputs.Various approaches for compressing three-dimensional images are suggested. Expand
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