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Artificial Intelligence
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Article
Undersampling based on generalized learning vector quantization and natural nearest neighbors for imbalanced data
Imbalanced datasets can adversely affect classifier performance. Conventional undersampling approaches may lead to the loss of essential information, while oversampling techniques could introduce noise. To add...
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Linear complexity of two classes of quaternary sequences based on sign alternation transformation
Two classes of optimal quaternary sequences have been constructed by applying the sign alternation transform and Gray map** to Legendre sequence pair, twin-prime sequence pair and GMW sequence pair. In this ...
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Integrated self-supervised label propagation for label imbalanced sets
Label propagation is an essential graph-based semi-supervised learning algorithm. However, the algorithm has two problems: how to effectively measure sample similarity and handle label imbalanced sets. Recent ...
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Open AccessTransfer metric learning: algorithms, applications and outlooks
Distance metric learning (DML) aims to find an appropriate way to reveal the underlying data relationship. It is critical in many machine learning, pattern recognition and data mining algorithms, and usually r...
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An empirical study of data sampling techniques for just-in-time software defect prediction
Just-in-time software defect prediction (JIT-SDP) is a fine-grained, easy-to-trace, and practical method. Unfortunately, JIT-SDP usually suffers from the class imbalance problem, which affects the performance ...
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Context-aware generative prompt tuning for relation extraction
Relation extraction is designed to extract semantic relation between predefined entities from text. Recently, prompt tuning has achieved promising results in the field of relation extraction, and its core idea...
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Enhanced feature pyramid for multi-view stereo with adaptive correlation cost volume
Multi-level features are commonly employed in the cascade network, which is currently the dominant framework in multi-view stereo (MVS). However, there is a potential issue that the recent popular multi-level ...
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Tensor low-rank representation combined with consistency and diversity exploration
In recent years, many tensor data processing methods have been proposed. Tensor low-rank representation (TLRR) is a recently proposed tensor-based clustering method that has shown good clustering performance i...
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Open AccessIntelligent analysis of android application privacy policy and permission consistency
With the continuous development of mobile devices, mobile applications bring a lot of convenience to people’s lives. The abuse of mobile device permissions is prone to the risk of privacy leakage. The existing...
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Diff-Font: Diffusion Model for Robust One-Shot Font Generation
Font generation presents a significant challenge due to the intricate details needed, especially for languages with complex ideograms and numerous characters, such as Chinese and Korean. Although various few-s...
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STOD: toward semi-supervised tiny object detection
Semi-supervised object detection aims to enhance object detectors by utilizing a large number of unlabeled images, which has gained increasing attention in natural scenes. However, when these methods are direc...
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Retraction Note: Placement delivery array design for the coded caching scheme in medical data sharing
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Generation, augmentation, and alignment: a pseudo-source domain based method for source-free domain adaptation
Source-free domain adaptation (SFDA) aims to train a well-performed model in the target domain given both a trained source model and unlabeled target samples. Although achieving remarkable progress, existing S...
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Open AccessTemporal-spatial deciphering mental subtraction in the human brain
Mental subtraction, involving numerical processing and operation, requires a complex interplay among several brain regions. Diverse studies have utilized scalp electroencephalograph, electrocorticogram, or fun...
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Electricity-cost-aware multi-workflow scheduling in heterogeneous cloud
Multi-workflows are commonly deployed on cloud platforms to achieve efficient computational power. Diverse task configuration requirements, the heterogeneous nature and dynamic electricity price of cloud serve...
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Semantic-enhanced reasoning question answering over temporal knowledge graphs
Question Answering Over Temporal Knowledge Graphs (TKGQA) is an important topic in question answering. TKGQA focuses on accurately understanding questions involving temporal constraints and retrieving accurate...
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A plug-and-play noise-label correction framework for unsupervised domain adaptation person re-identification
Unsupervised domain adaptation person re-identification (UDA ReID) aims at leveraging knowledge from the source domain to help perform ReID in the unlabeled target domain. Most of existing investigations usual...
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Incorporating bidirectional feature pyramid network and lightweight network: a YOLOv5-GBC distracted driving behavior detection model
Distracted driving is one of the leading causes of traffic accidents and has become a bottleneck for improving driver assistance technologies. It is still a challenge to detect distracted driving behavior in r...
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English letter recognition based on adaptive optimization spiking neural P systems
The novel dynamic guider algorithm within the adaptive optimization spiking neural P system (AOSNPS) framework is employed to create an innovative English letter recognition algorithm. This algorithm utilizes ...
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A zeroing feedback gradient-based neural dynamics model for solving dynamic quadratic programming problems with linear equation constraints in finite time
Gradient-based neural dynamics (GND) models are a classical algorithm for solving optimization problems, but it has non-negligible flaws in solving dynamic problems. In this study, a novel GND model, namely th...
