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

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樓主: HIV763
31#
發(fā)表于 2025-3-26 21:11:06 | 只看該作者
Projected Entangled Pair State Tensor Network for?Colour Image and?Video Completionring. However, a more general tensor model known as the projected entangled pair state (PEPS) tensor network has not been widely considered for colour image and video processing, although it has long been studied in quantum physics. In this study, we constructed the relationship between the generali
32#
發(fā)表于 2025-3-27 04:00:38 | 只看該作者
Artificial Neural Networks for?Downbeat Estimation and?Varying Tempo Induction in?Music Signalssic audio signals. Yet, this mechanism is not straightforward for automated systems and requires further scientific depiction. As automatic music analysis is a crucial step for music structure discovery and music recommendation, downbeat tracking and varying tempo induction have been persistent chal
33#
發(fā)表于 2025-3-27 05:32:30 | 只看該作者
34#
發(fā)表于 2025-3-27 10:23:20 | 只看該作者
35#
發(fā)表于 2025-3-27 14:03:54 | 只看該作者
External Knowledge and?Data Augmentation Enhanced Model for?Chinese Short Text Matchingask of natural language processing, but it still faces challenges such as ambiguity in Chinese words and imbalanced ratio of samples in the training set. To address these problems, we propose an external knowledge and data augmentation enhanced model (EDM) for Chinese short text matching. EDM uses j
36#
發(fā)表于 2025-3-27 18:01:40 | 只看該作者
37#
發(fā)表于 2025-3-27 22:02:47 | 只看該作者
Local-Global Interaction and?Progressive Aggregation for?Video Salient Object Detection that are not well handled in VSOD. First, facing unequal and unreliable spatio-temporal information in complex scenes, existing methods only exploit local information from different hierarchies for interaction and neglect the role of global saliency information. Second, they pay little attention to
38#
發(fā)表于 2025-3-28 02:49:08 | 只看該作者
A Fast Stain Normalization Network for?Cervical Papanicolaou Imagese the gap, color normalization is a prerequisite for most CAD algorithms. The existing algorithms with better normalization effect often require more computational consumption, resisting the fast application in large-size medical stain slide images. This paper designs a fast normalization network (F
39#
發(fā)表于 2025-3-28 08:53:36 | 只看該作者
: Evading Ownership Detection Against Deep Learning Modelsroperty (IP), and it is very important to defend against the model stealing attack. Recently, a well-known approach named Dataset Inference (DI) claimed that by measuring the distance from the sample to the decision boundary, it can be determined whether the theft has occurred..In this paper, we sho
40#
發(fā)表于 2025-3-28 11:52:05 | 只看該作者
Spatial-Temporal Graph Transformer for?Skeleton-Based Sign Language Recognitionus studies mainly employ hand-craft features or the spatial-temporal graph convolution networks for skeleton modality and neglect the importance of capturing the information between distant nodes and the long-term context in CSLR. To learn more robust spatial-temporal features for CSLR, we propose a
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