Key n-Gram Extractions and Analyses of Different Registers Based on Attention Network by Haiyan Wu, Ying Liu, Shaoyun Shi, Qingfeng Wu, Yunlong Huang

“…By summarizing the advantages and disadvantages of existing models, we propose a novel key n-gram extraction model “attentive n-gram network” (ANN) based on the attention mechanism and multilayer perceptron, in which the attention mechanism scores each n-gram in a sentence by mining the internal semantic relationship between words, and their importance is given by the scores. …”
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Attention and sentiment of Chinese public toward rural landscape based on Sina Weibo by Jinji Zhang, Guanghu Jin, Yang Liu, Xiyue Xue

“…The research reveals that the Chinese public’s attention to rural landscapes has significantly increased with the evolution of government governance concepts. …”
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Intrusion detection model of random attention capsule network based on variable fusion by Xinglan ZHANG, Shenglin YIN

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Semantic-enhanced panoptic scene graph generation through hybrid and axial attentions by Xinhe Kuang, Yuxin Che, Huiyan Han, Yimin Liu

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An Attention-Based Multidimensional Fault Information Sharing Framework for Bearing Fault Diagnosis by Yunjin Hu, Qingsheng Xie, Xudong Yang, Hai Yang, Yizong Zhang

“…Aiming at the above problems, this paper proposes an Attention-based Multidimensional Fault Information Sharing (AMFIS) framework, which aims to overcome the difficulties of multidimensional bearing fault diagnosis in a small sample environment. …”
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Enhancing bowel sound recognition with self-attention and self-supervised pre-training. by Yansuo Yu, Mingwu Zhang, Zhennian Xie, Qiang Liu

“…Our approach integrates the Branchformer architecture, which leverages the power of self-attention and convolutional gating for robust feature extraction, with a self-supervised pre-training strategy. …”
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Efficient Lane Detection Technique Based on Lightweight Attention Deep Neural Network by Zhiting Yao, Xiyuan Chen

“…Based on the attributes of disparate feature resolution characteristics, different attention mechanisms are adopted to guide the network to effectively exploit the model parameters. …”
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Prenatal Acetaminophen Exposure and its Associated Risk for Attention Deficit Hyperactivity Disorder by Noah J. Spillers, Norris C. Talbot, Patrick M. Luther, Gianni H. Ly, Caylin J. Roberts, Shahab Ahmadzadeh, Sahar Shekoohi, Omar Viswanath, Alan D. Kaye

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Multi scale multi attention network for blood vessel segmentation in fundus images by Giri Babu Kande, Madhusudana Rao Nalluri, R. Manikandan, Jaehyuk Cho, Sathishkumar Veerappampalayam Easwaramoorthy

“…In this paper, we introduce a novel approach, the MSMA Net model, which overcomes these challenges by replacing traditional convolution blocks and skip connections with an improved multi-scale squeeze and excitation block (MSSE Block) and Bottleneck residual paths (B-Res paths) with spatial attention blocks (SAB). Our experimental findings on publicly available datasets of fundus images, specifically DRIVE, STARE, CHASE_DB1, HRF and DR HAGIS consistently demonstrate that our approach outperforms other segmentation techniques, achieving higher accuracy, sensitivity, Dice score, and area under the receiver operator characteristic (AUC) in the segmentation of blood vessels with different thicknesses, even in situations involving diverse contextual information, the presence of coexisting lesions, and intricate vessel morphologies.…”
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Medical image segmentation based on frequency domain decomposition SVD linear attention by Liu Qiong, Li Chaofan, Teng Jinnan, Chen Liping, Song Jianxiang

“…During attention feature computation, we introduce Singular Value Decomposition (SVD) to extract an effective representation matrix from the original image, which is then applied in the attention computation process for linear projection. …”
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An attention based residual U-Net with swin transformer for brain MRI segmentation by Tazkia Mim Angona, M. Rubaiyat Hossain Mondal

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Concatenated Attention: A Novel Method for Regulating Information Structure Based on Sensors by Zeyu Zhang, Tianqi Chen, Yuki Todo

Subjects: “…self-attention…”
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An Optimized Deep-Learning-Based Network with an Attention Module for Efficient Fire Detection by Muhammad Altaf, Muhammad Yasir, Naqqash Dilshad, Wooseong Kim

“…In the subsequent phase, the proposed network utilizes an attention-based deep neural network (DNN) named Xception for detailed feature selection while reducing the computational cost, followed by adaptive spatial attention (ASA) to further enhance the model’s focus on a relevant spatial feature in the training data. …”
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The Dynamics of the Relationship between Attention Deficit Hyperactivity Disorder and Alcohol Use Disorder by Sevda Acar, Yeliz Aktaş

“…Attention-deficit hyperactivity disorder is defined as a neurodevelopmental disorder that begins in child- hood and persists into adulthood. …”
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Constructing Attention-LSTM-VAE Power Load Model Based on Multiple Features by Chaoyue Ma, Ying Wang, Feng Li, Huiyan Zhang, Yong Zhang, Haiyan Zhang

“…This paper proposes a variational autoencoder (VAE) long short-term memory (LSTM) load model based on the attention mechanism (Attention). First, the Prophet data decomposition method is used to decompose long sequences of load data at multiple time scales. …”
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Efficient Spectral-Spatial Fusion With Multiscale and Adaptive Attention for Hyperspectral Image Classification by Xiaoqing Wan, Feng Chen, Weizhe Gao, Yupeng He, Hui Liu, Zhize Li

Subjects: “…Attention mechanism…”
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Spatiotemporal dynamic and regional differences of public attention to vaccination: An empirical study in China. by Yaming Zhang, Xiaoyu Guo, Yanyuan Su

“…First, there are significant seasonal fluctuations and unbalanced monthly distributions of vaccination-related public attention in China. Second, the public attention in Chinese cities shows the spatial characteristics of "leading in the east, followed by the central, western and northeastern regions". …”
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Forecasting Stock Market Indices Using Integration of Encoder, Decoder, and Attention Mechanism by Tien Thanh Thach

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Long-term mindfulness meditation increases occurrence of sensory and attention brain states by Daniel Yochai Panitz, Daniel Yochai Panitz, Daniel Yochai Panitz, Avi Mendelsohn, Avi Mendelsohn, Avi Mendelsohn, Joana Cabral, Joana Cabral, Joana Cabral, Aviva Berkovich-Ohana, Aviva Berkovich-Ohana

“…These findings suggest that, by shifting attention toward enhanced sensory and embodied processing, MM effectively modulates the expression of functional network states at rest. …”
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Research on Gear Early Wear Fault Diagnosis Based on the Sparse Attention Mechanism by Gao Yunduan, Tian Ye, Zhu Yongbo, Li He, Zhang Jinjie

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