Attentive Self-supervised Contrastive Learning (ASCL) for plant disease classification by Getinet Yilma, Mesfin Dagne, Mohammed Kemal Ahmed, Ravindra Babu Bellam

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Alpha and Theta Oscillations Associated With Behavioral Phenotypes of Pain–Attention Interaction by Nikou Kelardashti, Benjamin T. Dunkley, Rima El‐Sayed, Vaidhehi Veena Sanmugananthan, Junseok Andrew Kim, Natalie Rae Osborne, Joshua C. Cheng, Anton Rogachov, Rachael L. Bosma, Ariana E. Besik, Karen Deborah Davis

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Attention-Guided Shared Hybrid Network for Enhanced Land Cover Segmentation by Yinbing Jiang, Linfeng Shi, Xinyu Fan

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Model-enhanced spatial-temporal attention networks for traffic density prediction by Qi Guo, Qi Tan, Yue Peng, Long Xiao, Miao Liu, Benyun Shi

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Brain CT image classification based on mask RCNN and attention mechanism by Shoulin Yin, Hang Li, Lin Teng, Asif Ali Laghari, Ahmad Almadhor, Michal Gregus, Gabriel Avelino Sampedro

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Auditory attention decoding based on neural-network for binaural beamforming applications by Roy Gueta, Elana Zion-Golumbic, Jacob Goldberger, Sharon Gannot

Subjects: “…audio attention decoding…”
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Development of the relationship between visual selective attention and auditory change detection by Yuanjun Kong, Xuye Yuan, Yiqing Hu, Bingkun Li, Dongwei Li, Jialiang Guo, Meirong Sun, Yan Song

Subjects: “…Visual selective attention…”
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Class-aware feature attention-based semantic segmentation on hyperspectral images. by Prabu Sevugan, Venkatesan Rudhrakoti, Tai-Hoon Kim, Megala Gunasekaran, Swarnalatha Purushotham, Ravikumar Chinthaginjala, Irfan Ahmad, Kumar A

“…Aclass-aware feature-based attention approach is combined with an enhanced attention-based network, FAttNet is proposed to segment the hyperspectral images semantically. …”
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Emotion recognition in conversations based on discourse parsing and graph attention network by HAO Xiulan, WEI Shaohua, CAO Qian, ZHANG Xiongtao

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MAGAN: Unsupervised Low-Light Image Enhancement Guided by Mixed-Attention by Renjun Wang, Bin Jiang, Chao Yang, Qiao Li, Bolin Zhang

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Characterization of the Process of Attention to Hypertensive People in a Cerro Municipality Polyclinic by Marilyn Hernández Sánchez, Addys Díaz Piñera, Armando Rodríguez Salvá, Mayté Más Gómez, Hortensia Cueto Lamar

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Relationships between Defects of Related Ability and Joint Attention of Children with Autism by Yumei CHEN, Zhenping LIN, Hong WANG, Jiewen CHEN, Weixin HUANG

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An intrusion detection method based on depthwise separable convolution and attention mechanism by Zhifei ZHANG, Feng LIU, Yiyang GE, Shuo LI, Yu ZHANG, Ke XIONG

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Identification of Maize Diseases Based on Dynamic Convolution and Tri-Attention Mechanism by Feilong Tang, Rosalyn R. Porle, Hoe Tung Yew, Farrah Wong

Subjects: “…Attention mechanism…”
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Pavement Disease Visual Detection by Structure Perception and Feature Attention Network by Bin Lv, Shuo Zhang, Haixia Gong, Hongbo Zhang, Bin Dong, Jianzhu Wang, Cong Du, Jianqing Wu

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Crochet increases attention through a requiring motor skill learning by Davide Rossi Sebastiano, Cristina Muscio, Dunja Duran, Deborah Bonfoco, Sara Dotta, Paola Anversa, Elisa Pellencin, Pietro Tiraboschi, Elisa Visani

“…Abstract In this study, we compared the effects promoted by a brief single session of crochet in a group of skilled knitters (CRO) and a control group (CRT) on the Attentional Network Test (ANT) and the whole brain Functional Connectivity (FC) revealed by Magnetoencephalography (MEG). …”
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Multi-Attention Fusion Modeling for Sentiment Analysis of Educational Big Data by Guanlin Zhai, Yan Yang, Heng Wang, Shengdong Du

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Relation Classification via Recurrent Neural Network with Attention and Tensor Layers by Runyan Zhang, Fanrong Meng, Yong Zhou, Bing Liu

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A hybrid attention generative adversarial network for Chinese landscape painting by Qiongshuai Lyu, Na Zhao, Zhiyuan Sun, Yu Yang, Chi Zhang, Ruolin Shi

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Graph-Attention Diffusion for Enhanced Multivariate Time-Series Anomaly Detection by Vadim Lanko, Ilya Makarov

“…Recently, among the unsupervised methods, diffusion models have attracted increased attention among researchers for addressing this particular task. …”
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