641 research outputs found

    Aesthetically Relevant Image Captioning

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    Image aesthetic quality assessment (AQA) aims to assign numerical aesthetic ratings to images whilst image aesthetic captioning (IAC) aims to generate textual descriptions of the aesthetic aspects of images. In this paper, we study image AQA and IAC together and present a new IAC method termed Aesthetically Relevant Image Captioning (ARIC). Based on the observation that most textual comments of an image are about objects and their interactions rather than aspects of aesthetics, we first introduce the concept of Aesthetic Relevance Score (ARS) of a sentence and have developed a model to automatically label a sentence with its ARS. We then use the ARS to design the ARIC model which includes an ARS weighted IAC loss function and an ARS based diverse aesthetic caption selector (DACS). We present extensive experimental results to show the soundness of the ARS concept and the effectiveness of the ARIC model by demonstrating that texts with higher ARS's can predict the aesthetic ratings more accurately and that the new ARIC model can generate more accurate, aesthetically more relevant and more diverse image captions. Furthermore, a large new research database containing 510K images with over 5 million comments and 350K aesthetic scores, and code for implementing ARIC are available at https://github.com/PengZai/ARIC.Comment: Aceepted by AAAI2023. Code and results available at https://github.com/PengZai/ARI

    Finite element modeling and active vibration control of high-speed spinning flexible beam

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    Finite element modeling and active vibration control of a high-speed spinning flexible coupled electromechanical beam is investigated using a first-order approximation coupling (FOAC) model. Due to centrifugal forces caused by eccentricity in a spinning flexible beam, there exists coupling between axial and transverse vibration modes. The partial differential equations of motion of the beam governing this coupling are derived using Hamilton’s principle based on an FOAC model, and a finite element method for discretization is given. It is observed that the zero-order approximate coupling (ZOAC) model is valid for dynamic description of the flexible beam spinning at low speeds, but no longer valid at high speeds. However, the validity of FOAC model is confirmed at different speeds. Piezoelectric elements for active vibration control of the spinning flexible beam are analyzed and a velocity feedback controller is proposed. Simulation results demonstrate good performance of the proposed velocity feedback controller

    Super-resolving Compressed Images via Parallel and Series Integration of Artifact Reduction and Resolution Enhancement

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    In this paper, we propose a novel compressed image super resolution (CISR) framework based on parallel and series integration of artifact removal and resolution enhancement. Based on maximum a posterior inference for estimating a clean low-resolution (LR) input image and a clean high resolution (HR) output image from down-sampled and compressed observations, we have designed a CISR architecture consisting of two deep neural network modules: the artifact reduction module (ARM) and resolution enhancement module (REM). ARM and REM work in parallel with both taking the compressed LR image as their inputs, while they also work in series with REM taking the output of ARM as one of its inputs and ARM taking the output of REM as its other input. A unique property of our CSIR system is that a single trained model is able to super-resolve LR images compressed by different methods to various qualities. This is achieved by exploiting deep neural net-works capacity for handling image degradations, and the parallel and series connections between ARM and REM to reduce the dependency on specific degradations. ARM and REM are trained simultaneously by the deep unfolding technique. Experiments are conducted on a mixture of JPEG and WebP compressed images without a priori knowledge of the compression type and com-pression factor. Visual and quantitative comparisons demonstrate the superiority of our method over state-of-the-art super resolu-tion methods.Code link: https://github.com/luohongming/CISR_PS

    Current-Induced Dynamics and Chaos of Antiferromagnetic Bimerons

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    A magnetic bimeron is a topologically non-trivial spin texture carrying an integer topological charge, which can be regarded as the counterpart of skyrmion in easy-plane magnets. The controllable creation and manipulation of bimerons are crucial for practical applications based on topological spin textures. Here, we analytically and numerically study the dynamics of an antiferromagnetic bimeron driven by a spin current. Numerical simulations demonstrate that the spin current can create an isolated bimeron in the antiferromagnetic thin film via the damping-like spin torque. The spin current can also effectively drive the antiferromagnetic bimeron without a transverse drift. The steady motion of an antiferromagnetic bimeron is analytically derived and is in good agreement with the simulation results. Also, we find that the alternating-current-induced motion of the antiferromagnetic bimeron can be described by the Duffing equation due to the presence of the nonlinear boundary-induced force. The associated chaotic behavior of the bimeron is analyzed in terms of the Lyapunov exponents. Our results demonstrate the inertial dynamics of an antiferromagnetic bimeron, and may provide useful guidelines for building future bimeron-based spintronic devices.Comment: 6 pages, 4 figure

    Back-action Induced Non-equilibrium Effect in Electron Charge Counting Statistics

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    We report our study of the real-time charge counting statistics measured by a quantum point contact (QPC) coupled to a single quantum dot (QD) under different back-action strength. By tuning the QD-QPC coupling or QPC bias, we controlled the QPC back-action which drives the QD electrons out of thermal equilibrium. The random telegraph signal (RTS) statistics showed strong and tunable non-thermal-equilibrium saturation effect, which can be quantitatively characterized as a back-action induced tunneling out rate. We found that the QD-QPC coupling and QPC bias voltage played different roles on the back-action strength and cut-off energy.Comment: 4 pages, 4 figures, 1 tabl
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