The proliferation of Automated Teller Machines (ATMs) in the banking sector has raised the stakes in identifying the most suitable locations for these machines, given their impact on the profitability and satisfaction...
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Graph wavelet neural network, as a popular method of graph neural networks, has achieved good result in representation learning. However, graph wavelet neural network faces the phenomenon of over-smoothing, which mean...
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As the most important module in recommendation systems, click-through rate prediction has attracted the attention of industry and academia. Due to the powerful learning ability of deep learning, it is widely used in c...
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Expression of programmed death ligand-1 is a meaningful biomarker for identifying treatments to tumor patients involved non-small cell lung cancer (NSCLC). Tumor proportion score (TPS) is an essential indexes to descr...
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Physical adversarial attacks directly apply adversarial perturbations to real-world objects. Perturbations usually are printed as patches and pasted on target objects. This requires attackers in the vicinity of target...
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Irregular boundaries in image stitching naturally occur due to freely moving *** deal with this problem,existing methods focus on optimizing mesh warping to make boundaries regular using the traditional explicit ***,p...
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Irregular boundaries in image stitching naturally occur due to freely moving *** deal with this problem,existing methods focus on optimizing mesh warping to make boundaries regular using the traditional explicit ***,previous methods always depend on hand-crafted features(e.g.,keypoints and line segments).Thus,failures often happen in overlapping regions without distinctive *** this paper,we address this problem by proposing RecStitchNet,a reasonable and effective network for image stitching with rectangular *** that both stitching and imposing rectangularity are non-trivial tasks in the learning-based framework,we propose a three-step progressive learning based strategy,which not only simplifies this task,but gradually achieves a good balance between stitching and imposing *** the first step,we perform initial stitching by a pre-trained state-of-the-art image stitching model,to produce initially warped stitching results without considering the boundary ***,we use a regression network with a comprehensive objective regarding mesh,perception,and shape to further encourage the stitched meshes to have rectangular boundaries with high content ***,we propose an unsupervised instance-wise optimization strategy to refine the stitched meshes iteratively,which can effectively improve the stitching results in terms of feature alignment,as well as boundary and structure *** to the lack of stitching datasets and the difficulty of label generation,we propose to generate a stitching dataset with rectangular stitched images as pseudo-ground-truth labels,and the performance upper bound induced from the it can be broken by our unsupervised *** and quantitative results and evaluations demonstrate the advantages of our method over the state-of-the-art.
Facial expression recognition (FER) is a challenging task. The following two significant problems often exist in real-life FER tasks: first, facial expression images in the wild are uncertain, i.e., occlusion or blurr...
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Federated Learning (FL) is a distributed approach for performing machine learning tasks. It prevents data sharing by aggregating the models trained by distributed clients on the central server, thereby maintaining dat...
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In this paper, the application of image processing and machine learning in object recognition is studied. Firstly, a calculation method based on color, size and leaf area ratio is proposed. Through image preprocessing...
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Gene expression profiles play a significant role in drug research. If the gene expression profile under the action of drugs can be obtained quickly, such as through computational methods, the analysis of the relations...
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