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   Articles with "head attention" as a keyword



Hierarchical multi-head attention LSTM for polyphonic symbolic melody generation

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recommendations! Published in 2024 at "Multimedia Tools and Applications"

DOI: 10.1007/s11042-024-18491-7

Abstract: Creating symbolic melodies with machine learning is challenging because it requires an understanding of musical structure and the handling of inter-dependencies and long-term dependencies. Learning the relationship between events that occur far apart in time… read more here.

Keywords: polyphonic symbolic; hierarchical multi; attention lstm; head attention ... See more keywords
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On the diversity of multi-head attention

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recommendations! Published in 2021 at "Neurocomputing"

DOI: 10.1016/j.neucom.2021.04.038

Abstract: Abstract Multi-head attention is appealing for the ability to jointly attend to information from different representation subspaces at different positions. In this work, we propose two approaches to better exploit such diversity for multi-head attention,… read more here.

Keywords: attention; diversity multi; head; head attention ... See more keywords
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Intelligent Bearing Fault Diagnosis Using Multi-Head Attention-Based CNN

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recommendations! Published in 2020 at "Procedia Manufacturing"

DOI: 10.1016/j.promfg.2020.07.005

Abstract: Abstract Aiming at automatic feature extraction and fault recognition of rolling bearings, a new data-driven intelligent fault diagnosis approach using multi-head attention and convolutional neural network (CNN) is proposed. Firstly, a simple signal-to-image spatial transform… read more here.

Keywords: fault; multi head; diagnosis; bearing fault ... See more keywords

Performance prediction of sintered NdFeB magnet using multi-head attention regression models

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recommendations! Published in 2024 at "Scientific Reports"

DOI: 10.1038/s41598-024-79435-7

Abstract: The preparation of sintered NdFeB magnets is complex, time-consuming, and costly. Data-driven machine learning methods can enhance the efficiency of material synthesis and performance optimization. Traditional machine learning models based on mathematical and statistical principles… read more here.

Keywords: attention; ndfeb magnet; head attention; sintered ndfeb ... See more keywords

Heuristically enhanced multi-head attention based recurrent neural network for denial of wallet attacks detection on serverless computing environment

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-87636-x

Abstract: Denial of Wallet (DoW) attacks are a cyber threat designed to utilize and deplete an organization’s financial resources by generating excessive prices or charges in their cloud computing (CC) and serverless computing platforms. These threats… read more here.

Keywords: detection; denial wallet; serverless computing; serverless ... See more keywords

Enhanced Mamba model with multi-head attention mechanism and learnable scaling parameters for remaining useful life prediction

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-91815-1

Abstract: Prognostics and health management (PHM) technology aims to analyze and diagnose the state of equipment using a large amount of data, predict potential failures, and adopt corresponding maintenance and repair strategies to enhance equipment reliability,… read more here.

Keywords: attention mechanism; prediction; model; head attention ... See more keywords

An intelligent ransomware based cyberthreat detection model using multi head attention-based recurrent neural networks with optimization algorithm in IoT environment

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-92711-4

Abstract: The rapid growth of the Internet of Things (IoT) and its extensive use in many regions, such as smart homes, healthcare, and vehicles, have made IoT security increasingly critical. Ransomware is an advanced and adjustable… read more here.

Keywords: ransomware; model; head attention; ransomware detection ... See more keywords

GTKNet: a transformer-based graph neural network for predicting molecular properties with KAN and multi-head attention

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recommendations! Published in 2025 at "Molecular Simulation"

DOI: 10.1080/08927022.2025.2523073

Abstract: ABSTRACT With the advancement of science and technology, the application of artificial intelligence in the field of materials science has become a research hotspot, particularly in molecular property prediction and material design. This study proposes… read more here.

Keywords: based graph; gtknet; attention; transformer based ... See more keywords

Classification of ECG using ensemble of residual CNNs with or without attention mechanism

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recommendations! Published in 2022 at "Physiological Measurement"

DOI: 10.1088/1361-6579/ac647c

Abstract: Objective. This paper introduces a winning solution (team ISIBrno-AIMT) to the official round of PhysioNet Challenge 2021. The main goal of the challenge was a classification of ECG recordings into 26 multi-label pathological classes with… read more here.

Keywords: attention mechanism; classification; multi head; head attention ... See more keywords

Triple Channel Feature Fusion Few-Shot Intent Recognition With Orthogonality Constrained Multi-Head Attention

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recommendations! Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2024.3369902

Abstract: Intent recognition in few-shot scenarios is a hot research topic in natural language understanding tasks. Aiming at the problems of insufficient consideration of fine-grained features of the text and insufficient training of features in the… read more here.

Keywords: intent recognition; triple channel; head attention; multi head ... See more keywords

An Augmented AutoEncoder With Multi-Head Attention for Tool Wear Prediction in Smart Manufacturing

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recommendations! Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2024.3406568

Abstract: Computer numerical control (CNC) machine tools play a crucial role in the manufacturing industry, and cutting tools, as key functional components, directly impact the quality of the machining process. An improved autoEncoder with multi-head attention… read more here.

Keywords: tool wear; attention; head attention; multi head ... See more keywords