Titlebook: Neural Information Processing; 29th International C Mohammad Tanveer,Sonali Agarwal,Adam Jatowt Conference proceedings 2023 The Editor(s) (

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Thomas Ranvier,Haytham Elgazel,Emmanuel Coquery,Khalid Benabdeslems guided us towards a solution based on the software product line paradigm. Multiple options can be easily incorporated to each product, allowing the adequate customization of the final application to the disability of each concrete person. Software product lines are a proven development paradigm in

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paroxysm

Artificial Neural Networks for Downbeat Estimation and Varying Tempo Induction in Music Signalsent neural networks to distinguish downbeat instants, supported by a dynamic Bayesian network to jointly infer the tempo estimation and correct the estimated downbeat locations according to the optimal solution. The proposed system outperforms existing algorithms with an achieved F1 score of 88.0%.

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Bottom-Up Transformer Reasoning Network for Text-Image Retrieval the image and text separately. We also embed the tag information generated by Faster-RCNN to strengthen the connection between the two modalities. Recall at K and normalized discounted cumulative gain metric (NDCG) metrics are used to evaluate our model. Through various experiments, we prove our model can reach state-of-the-art results.

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Autoencoder-Based Attribute Noise Handling Method for Medical Datantly exists to entirely handle attribute noise in tabular data. We experimentally demonstrate that our method outperforms both state-of-the-art imputation methods and noise correction methods on several real-world medical datasets.

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