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Dual-attention Network for View-invariant Action Recognition
View-invariant action recognition has been widely researched in various applications, such as visual surveillance and human–robot interaction....
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Linear Time Invariant Systems
We assume the reader to have familiarity with linear time-invariant (LTI) systems. In this chapter we merely summarise the main results of this...
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Molecular set representation learning
Computational representation of molecules can take many forms, including graphs, string encodings of graphs, binary vectors or learned embeddings in...
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Multiple Model Switching Control of Linear Time-Invariant Systems
In this article, multiple model switching controller was proposed to regulate the motion modes of a linear time-invariant system. Frequency domain of...
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Linear Time-Invariant Systems and Stability
To assess the stability properties of the aeroelastic system, the equations are often cast in linear time-invariant form. This chapter introduces the...
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On the lifting and reconstruction of nonlinear systems with multiple invariant sets
The Koopman operator provides a linear perspective on non-linear dynamics by focusing on the evolution of observables in an invariant subspace....
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Linear Time-Invariant Systems and Control
This chapter presents key classical control concepts and introduces state-space modeling and analysis of control systems as applied to the control of...
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Permutation invariant encodings for quantum machine learning with point cloud data
Quantum computing offers a potentially powerful new method for performing machine learning. However, several quantum machine learning techniques have...
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Conditioned Invariant Subspaces and the Geometry of Nilpotent Matrices
The focus of this work is on certain geometric aspects of the classification problems for invariant and conditioned invariant subspaces. In this...
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Scale-Invariant Fast Functional Registration
Functional registration algorithms represent point clouds as functions (e.g. spacial occupancy field) avoiding unreliable correspondence estimation...
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EEG emotion recognition framework based on invariant wavelet scattering convolution network
EEG signals for real-time emotion identification are crucial for affective computing and human-computer interaction. The current emotion recognition...
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The Invariant Integral on SO(3)
For a first reading, the reader may glance over the introductory remarks in Sect. 3.1, stop after reading Sect. 3.1.2, skip the proofs, accept...
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Invariant Measures for Contact Processes with State-Dependent Birth and Death Rates
We consider contact processes on locally compact separable metric spaces with birth and death rates that are heterogeneous in space. We formulate...
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Transformation guided representation GAN for pose invariant face recognition
Face recognition is an important topic in the field of computer vision and has been a vital biometric technique for identity authentication. It is...
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DIFLD: domain invariant feature learning to detect low-quality compressed face forgery images
With the rapid development of deep learning, face forgery detection methods have also achieved remarkable progress. However, most methods suffer...
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Observer-Based Output Feedback Control Using Invariant Polyhedral Sets for Fuzzy T–S Models Under Constraints
We propose a systematic design method to compute an observer-based output feedback controller for fuzzy Takagi–Sugeno (T–S) systems with unmeasurable...
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Dynamic texture description using adapted bipolar-invariant and blurred features
Encoding turbulent properties of dynamic textures (DTs) is a challenging issue of video understanding for various applications in computer vision. It...
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Fisher Discriminative Embedding Low-Rank Sparse Representation for Music Genre Classification
This work focuses on a music genre classification method based on a sparse low-rank representation. Sparse low-rank representation is an effective...
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Space–time flow computation with boundary layer and contact representation: a 10-year history
In computation of flow problems with moving solid surfaces, moving-mesh methods such as the space–time (ST) variational multiscale method enable...
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Universal and accent-discriminative encoders for conformer-based accent-invariant speech recognition
Accent-variation is a challenging issue, either for traditional hybrid or current end-to-end (E2E) automatic speech recognition (ASR). Building an...
