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In cardiovascular magnetic resonance (CMR), typical acquisitions often involve a limited number of short and long axis slices. However, reconstructing the 3D chambers is crucial for accurately quantifying heart geometry and assessing cardiac ...

Anatomical heart mesh models created from cine cardiac images are useful for the evaluation and monitoring of cardiovascular diseases, but require challenging and time-consuming reconstruction processes. Errors due to reduced spatial resolution ...

Continual relation extraction (CRE) aims to continually learn new relations while maintaining knowledge of previous relations in the data streams. Recently, continual few-shot relation extraction (CFRE) is introduced, in which only the first step ...

With the development of information technology, the intelligence level of the power system has been further enhanced, but it also poses challenges to the security of the power system. In order to ensure the safe operation of the power grid, a power ...

With the development of e-government, multiple local governments in China are developing Internet-based open policy platforms, and these online platforms need to automatically classify policies. Current policy classification methods are usually ...

• We propose a large-scale framework for multi-label policy classification.
• We propose a method for finding category-related seed words in an unlabeled corpus.
• We propose a string matching-based pseudo-label generation strategy.
• ...

Feature selection can eliminate irrelevant redundant information in high-dimensional data, reduce dimensions, improve classification performance, and relieve the computational burden of machine learning. In this paper, we propose a feature ...

Professional clothing design for high-temperature operations is an essential concern for industrial development. In this paper, for the existing layering of professional garments for high-temperature operations, the finite difference method is ...

The long-tail effect is a common issue that limits the performance of deep learning models on real-world datasets. Character image datasets are also affected by such unbalanced data distribution due to differences in character usage frequency. Thus, ...

In this work, we present details of the nanofabrication process for achieving a silicon nitride nanoelectromechanical resonator, consisting of a membrane covered with a thin aluminium layer capacitively coupled to a suspended top gate. ...

As online coding technology advances, various related products are emerging, but we observe that there are not many examples of introducing online coding into the field of theorem proving. We introduce Isabelle/Cloud, an online coding platform and user ...

Power transmission lines require efficient and reliable tree pruning to maintain their operation. This paper presents an adaptive Alternating Direction Method of Multipliers (ADMM)-based fast Model Predictive Control (MPC) for aerial tree pruning ...

Owing to the attractive properties of decentralization, unforgeability, transparency, and traceability, blockchain is increasingly being used in various scenarios such as supply chain and public services, where massive Spatial-Temporal-Keywords (STK) ...

Web3 brings an emerging outlook for the value of decentralization, boosting the decentralized infrastructure. People can benefit from Web3, facilitated by the advances in distributed ledger technology, to read, write and own web content, services and ...

• An end-to-end master-auxiliary cross-modality retrieval architecture.
• A novel Semantic Auxiliary Network (SAN) to enrich semantic attributes.
• A novel triplet rigid center loss function.
• The proposed method outperforms the state-...

Sketch-based 3D shape retrieval has always been a hot research topic in the computer vision community. The main challenge is to alleviate the cross-modality discrepancies such that the retrieval accuracies can be improved. In this paper, we ...

Emotion Recognition in Conversations (ERC) can capture the speakers’ emotional changes in multiple rounds of conversation, so it has a wide range of applications. In recent years, Graph Neural Networks have been naturally used in ERC tasks due to ...

• A method for apple growth morphology based on Mask RCNN + PointRend has been proposed.
• SPPF structure, CA attention mechanism and PANet are introduced as improvements.
• CWD algorithm is used for model distillation to improve the ...

Identifying apples with different growth forms is an urgent task to be solved by harvesting robots on the path to intelligence. A method based on Mask RCNN + PointRend was proposed for identifying apples with different growth forms in the orchard ...

• New decoding-based background filtering developed for roadside LiDAR applications.
• Filtering embeddings in decoding boosts speed without sacrificing accuracy.
• Static and dynamic background objects have been considered in background ...

This study is part of an investigation on application of LiDAR sensors to roadside to create a human-in-the-loop system that actively protects all road users, especially pedestrians and cyclists. The primary challenge for implementing such a ...

Cyber-attacks and network intrusion have surfaced as major concerns for modern days applications of the Internet of Things (IoT). The existing intrusion detection and prevention techniques have a wide range of limitations and thus are unable to ...

Most existing cross-domain intelligent fault diagnosis algorithms rely on many samples and only consider the global alignment of all faults. It is not practical to obtain numerous fault samples under actual working conditions. Therefore, it is a ...

The complexity and non-Euclidean structure of graph data hinders the development of data augmentation methods similar to those in computer vision. In this paper, we propose a feature augmentation method for graph nodes based on topological ...