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Fast data-independent KLT approximations based on integer functions
The Karhunen-Loève transform (KLT) stands as a well-established discrete transform, demonstrating optimal characteristics in data decorrelation and...
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A New Visual Front-end Combining KLT with Descriptor Matching for Visual-inertial Odometry
Currently, feature-based visual-inertial odometry (VIO) predominantly employs descriptor-matching or Kanade-Lucas-Tomasi (KLT)-based methods for...
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The KLT relation from the tree formula and permutohedron
In this paper, we generalize the Nguyen–Spradlin–Volovich–Wen (NSVW) tree formula from the MHV sector to any helicity sector. We find a close...
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Generalizations of the double-copy: the KLT bootstrap
We formulate a new program to generalize the double-copy of tree amplitudes. The approach exploits the link between the identity element of the “KLT...
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KLT factorization of nonrelativistic string amplitudes
We continue our study of the Kawai-Lewellen-Tye (KLT) factorization of winding string amplitudes in [1]. In a toroidal compactification, amplitudes...
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Emotion recognition of the driver based on KLT algorithm and ShuffleNet V2
Emotional monitoring was essential in the development of sophisticated automobiles with advanced driver assistance systems (ADAS) to ensure safety...
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Feature Matching Method Based on Improved SIFT and KLT
Feature extraction and matching are important aspects of monocular vision and key steps for autonomous flight of unmanned aerial vehicles. To address...
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On the design of KLT-based maximally incoherent deterministic sensing matrices for compressive sensing applied to wireless sensor networks data
The Compressive Sensing (CS) framework explores signal sparsity to reduce the amount of data to transmit or store. In it, signal projections on...
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Low-complexity rounded KLT approximation for image compression
The Karhunen–Loève transform (KLT) is often used for data decorrelation and dimensionality reduction. Because its computation depends on the matrix...
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A curvelet-based multi-sensor image denoising for KLT-based image fusion
The transform-based multi-sensor image denoising methods are inefficient in restoring fine details and texture information of noisy images. The fixed...
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KLT factorization of winding string amplitudes
We uncover a Kawai-Lewellen-Tye (KLT)-type factorization of closed string amplitudes into open string amplitudes for closed string states carrying...
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Finiteness of Real Structures on KLT Calabi–Yau Regular Smooth Pairs of Dimension 2
In this article, we prove that a smooth projective complex surface X which is regular (i.e. such that...
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On polytopes and generalizations of the KLT relations
We combine the technology of the theory of polytopes and twisted intersection theory to derive a large class of double copy relations that generalize...
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Decorrelation of a Sequence of Color Images Through Hierarchical Adaptive Color KLT
In this work is presented new algorithm for Hierarchical Adaptive Color Karhunen–Loève transform (HACKLT) aimed at the decorrelation of sequences of...
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KLT, A New Algorithm For SETI
In 1960, the astronomer Frank Drake listened to the stars Tau Ceti and Epsilon Eridani, searching for extra terrestrial intelligent signals: the so...
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Positivity of the CM line bundle for families of K-stable klt Fano varieties
The Chow–Mumford (CM) line bundle is a functorial line bundle on the base of any family of klt Fano varieties. It is conjectured that it yields a...
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KLT-CRKCN: Hyperspectral Image Classification via Karhunen Loeve Transformation and Collaborative Representation-Based K Closest Neighbor
Collaborative representation-based classification is extensively used in numerous application fields for e.g. hyperspectral image and face...
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The evaluation of Rolimeter, KLT, KiRA and KT-1000 arthrometer in healthy individuals shows acceptable intra-rater but poor inter-rater reliability in the measurement of anterior tibial knee translation
PurposeTo assess measurement equivalence, inter- and intra-rater reliability, standard error of measurements (SEM) and false positive measurements...
