Tooth instance segmentation is a key technology in the field of medical image segmentation, with applications ranging from orthodontic treatment to dental pathology assessment. Although researchers have developed many...
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In the process industries, it's hard to control a non-linear process. Nonlinear behavior is frequently seen in real processes. The challenging problem of controlling a spherical tank is result of its nonlinearity ...
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This article introduces a novel model for low-quality pedestrian trajectory prediction, the social nonstationary transformers (NSTransformers), that merges the strengths of NSTransformers and spatiotemporal graph tran...
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AC and DC hybrid power grids are widely used in the power industry due to the continuous development of energy systems. In this paper, the control strategy and stability analysis of MMC (Modular Multilevel Converter) ...
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To address the issues of low efficiency and difficulty in interval printing splicing in large-area stamping-based stereolithography, a print path planning method based on an improved ant colony algorithm is proposed. ...
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State-of-the-art NLP models have demonstrated exceptional performance across various tasks, including sentiment analysis. However, concerns have been raised about their robustness and susceptibility to systematic bias...
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Different from source coding, which only emphasizes coding efficiency, fault-tolerant coding adds some redundant information during coding to strengthen the ability of error resistance, so as to obtain the best gain w...
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Benefiting from the development of hyperspectral imaging technology,hyperspectral image(HSI)classification has become a valuable direction in remote sensing image ***,researchers have found a connection between convol...
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Benefiting from the development of hyperspectral imaging technology,hyperspectral image(HSI)classification has become a valuable direction in remote sensing image ***,researchers have found a connection between convolutional neural networks(CNNs)and Gabor ***,some Gabor-based CNN methods have been proposed for HSI ***,most Gabor-based CNN methods still manually generate Gabor filters whose parameters are empirically set and remain unchanged during the CNN learning ***,these methods require patch cubes as network *** patch cubes may contain interference pixels,which will negatively affect the classification *** address these problems,in this paper,we propose a learnable three-dimensional(3D)Gabor convolutional network with global affinity attention for HSI *** precisely,the learnable 3D Gabor convolution kernel is constructed by the 3D Gabor filter,which can be learned and updated during the training ***,spatial and spectral global affinity attention modules are introduced to capture more discriminative features between spatial locations and spectral bands in the patch cube,thus alleviating the interfering pixels *** results on three well-known HSI datasets(including two natural crop scenarios and one urban scenario)have demonstrated that the proposed network can achieve powerful classification performance and outperforms widely used machine-learning-based and deep-learning-based methods.
Dear Editor,This letter proposes a contrastive consensus graph learning model for multi-view *** are usually built to outline the correlation between multi-model objects in clustering task,and multiview graph clusteri...
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Dear Editor,This letter proposes a contrastive consensus graph learning model for multi-view *** are usually built to outline the correlation between multi-model objects in clustering task,and multiview graph clustering aims to learn a consensus graph that integrates the spatial property of each view.
This article used finite element (FE) analysis to study and analyze the electrical conductivity profile of simulated stroke patients based on a 45 dB signal-to-noise ratio synthesized measurement. Clinical measurement...
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