Seeing without the Occipito-Parietal Cortex: Simultagnosia as a Shrinkage of the Attentional Visual Field by François Michel, Marie-Anne Henaff

“…An experimental approach with tasks testing visuo-spatial attention demonstrated a shrinkage of A.T.’s attentional visual field. …”
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The effect of the strategy to nominate ideas on divided and selective attention and perform some volleyball skills by Fadya Abdul Hussein Kadhim, Alyaa Hussein Farhan, Tahseen Husnl Tahseen, Suhad Qassem Saeed Al-Mousawi, Haider Radhi Raheem

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Neural Networks for Operational SYM‐H Forecasting Using Attention and SWICS Plasma Features by Armando Collado‐Villaverde, Pablo Muñoz, Consuelo Cid

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Multi-modal feature fusion with multi-head self-attention for epileptic EEG signals by Ning Huang, Zhengtao Xi, Yingying Jiao, Yudong Zhang, Zhuqing Jiao, Xiaona Li

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Caption Generation Based on Emotions Using CSPDenseNet and BiLSTM with Self-Attention by Kavi Priya S, Pon Karthika K, Jayakumar Kaliappan, Senthil Kumaran Selvaraj, Nagalakshmi R, Baye Molla

“…The decoding unit employs a self-attention mechanism encompassed with BiLSTM to create more descriptive and relevant captions in natural language. …”
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Enhanced hybrid attention deep learning for avocado ripeness classification on resource constrained devices by Sumitra Nuanmeesri

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MultiChem: predicting chemical properties using multi-view graph attention network by Heesang Moon, Mina Rho

“…In our model, graph attention layers are employed to effectively capture essential local structures by jointly considering atom and bond features, while multi-head attention layers extract important global features. …”
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IEDSFAN: information enhancement and dynamic-static fusion attention network for traffic flow forecasting by Lianfei Yu, Ziling Wang, Wenxi Yang, Zhijian Qu, Chongguang Ren

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Deep BiLSTM Attention Model for Spatial and Temporal Anomaly Detection in Video Surveillance by Sarfaraz Natha, Fareed Ahmed, Mohammad Siraj, Mehwish Lagari, Majid Altamimi, Asghar Ali Chandio

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Physics-Constrained Deep Learning for Security Ink Colorimetry with Attention-Based Spectral Sensing by Po-Tong Wang, Chiu Wang Tseng, Li-Der Fang

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Energy consumption prediction using modified deep CNN-Bi LSTM with attention mechanism by Adel Binbusayyis, Mohemmed Sha

“…Deep CNN extracts features impacting energy consumption whereas Bi-LSTM with attention layer finds suitability for regression as it is capable of modelling irregular trends in the time-series components, where the attention mechanism is implemented to enhance the decoder's ability to selectively focus on the most relevant segments of the input sequence. …”
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A new method of distracting attention: Is it effective for pain and fear during phlebotomy in children? by Mine Aydemir Sahin, Yeliz Cigerci, Hamide Nur Cevik Ozdemir

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A listening advantage for native speech is reflected by attention-related activity in auditory cortex by Meng Liang, Johannes Gerwien, Alexander Gutschalk

“…Here we test the hypothesis that attentional enhancement in auditory cortex is stronger for native speech, using magnetoencephalography. …”
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CNFA: ConvNeXt Fusion Attention Module for Age Recognition of the Tangerine Peel by Fuqin Deng, Junwei Li, Lanhui Fu, Chuanbo Qin, Yikui Zhai, Hongmin Wang, Ningbo Yi, Nannan Li, TinLun Lam

“…This work investigates the automatic age recognition of the tangerine peel based on deep learning and attention mechanisms. We proposed an effective ConvNeXt fusion attention module (CNFA), which consists of three parts, a ConvNeXt block for extracting low-level features’ information and aggregating hierarchical features, a channel squeeze-and-excitation (cSE) block and a spatial squeeze-and-excitation (sSE) block for generating sufficient high-level feature information from both channel and spatial dimensions. …”
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Improving Medical Image Quality Using a Super-Resolution Technique with Attention Mechanism by Dong Yun Lee, Jang Yeop Kim, Soo Young Cho

Subjects: “…attention mechanism…”
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Multi-channel spatio-temporal graph attention contrastive network for brain disease diagnosis by Chaojun Li, Kai Ma, Shengrong Li, Xiangshui Meng, Ran Wang, Daoqiang Zhang, Qi Zhu

“…Second, we develop a multi-channel spatial attention contrastive network to extract topological features from the brain network within each time window. …”
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Multiscale attention network via topology learning for cerebral vessel segmentation in angiography images by Tao Han, Junchen Xiong, Tingyi Lin, Tao An, Cheng Wang, Jianjun Zhu, Zhongliang Li, Ligong Lu, Yi Zhang, Gao-Jun Teng

“…This method employs a Multiscale Squeeze Attention (MSA) module for channel-wise attention learning, extracting multiscale attention feature maps from angiographic images. …”
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An Effective Self-Attention-Based Hybrid Model for Short-Term Traffic Flow Prediction by Zhihong Li, Xiaoyu Wang, Kairan Yang

“…Our new hybrid model gives a higher accuracy than the support vector regression (SVR) model, LSTM neural network-attention (LSTM-attention) model, and temporal convolutional network (TCN) model. …”
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Enhanced oracle bone corrosion detection using attention-guided YOLO with ghost convolution by Feng Gao, Ziheng Yang, Qiyu Liu, Zhan Zhang, Bang Li, Han Zhang

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DMSS: An Attention-Based Deep Learning Model for High-Quality Mass Spectrometry Prediction by Yihui Ren, Yu Wang, Wenkai Han, Yikang Huang, Xiaoyang Hou, Chunming Zhang, Dongbo Bu, Xin Gao, Shiwei Sun

“…In this study, we introduce Deep MS Simulator (DMSS), a novel attention-based model tailored for forecasting theoretical spectra in mass spectrometry. …”
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