RaViT-AE: Unsupervised Anomaly Detection for Intelligent Cultural Heritage Monitoring Using Region-Attentive ViT Autoencoder by Dohyung Kwon, Jeongmin Yu

“…Region-attentive patch projection enhances detection by applying higher-dimensional embeddings to regions of petroglyph images that show a higher likelihood of anomalies, effectively extracting features and recognizing complex patterns. …”
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Traffic environment perception algorithm based on multi-task feature fusion and orthogonal attention by Zhengfeng LI, Mingen ZHONG, Yihong ZHANG, Kang FAN, Zhiying DENG, Jiawei TAN

“…The integration of complementary pattern information deepens feature sharing, thereby enhancing the recognition accuracy of each task. …”
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Attention Lempel-Ziv complexity: an improved Lempel-Ziv complexity with high computational efficiency for bearing early fault detection by Jiancheng Yin, Wentao Sui, Xuye Zhuang, Yunlong Sheng

“…Lempel-Ziv complexity assesses time series anomalies by quantifying the amount of novel patterns within the time series. It has been effectively utilized in assessing bearing fault severity and classification. …”
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Golden Chip-Free Hardware Trojan Detection Using Attention-Based Non-Local Convolution With Simple Recurrent Unit by Rama Devi Maddineni, Deepak Ch

“…The emergence of machine learning and deep learning models has enhanced the feasibility of hardware Trojan detection, as these models can learn complex patterns and representations from extensive datasets. …”
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Conv1D-GRU-Self Attention: An Efficient Deep Learning Framework for Detecting Intrusions in Wireless Sensor Networks by Kenan Honore Robacky Mbongo, Kanwal Ahmed, Orken Mamyrbayev, Guanghui Wang, Fang Zuo, Ainur Akhmediyarova, Nurzhan Mukazhanov, Assem Ayapbergenova

“…This study proposes a hybrid IDS model combining one-dimensional Convolutional Neural Networks (Conv1Ds), Gated Recurrent Units (GRUs), and Self-Attention mechanisms. A Conv1D extracts spatial features from network traffic, GRU captures temporal dependencies, and Self-Attention emphasizes critical sequence components, collectively enhancing detection of subtle and complex intrusion patterns. …”
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A deep learning approach for heart disease detection using a modified multiclass attention mechanism with BiLSTM by Umesh Kumar Lilhore, Sarita Simaiya, Monish Khan, Roobaea Alroobaea, Abdullah M. Baqasah, Majed Alsafyani, Afnan Alhazmi

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Local pattern aware 3D video swin transformer with masked autoencoding for realtime augmented reality gesture interaction by Suli Wang

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Multiscale Feature Fusion for Salient Object Detection of Strip Steel Surface Defects by Li Zhang, Xirui Li, Yange Sun, Yan Feng, Huaping Guo

“…These results demonstrate that the proposed approach not only enhances detection accuracy but also significantly improves the adaptability of the model to various defect patterns. …”
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Dual Transformers With Latent Amplification for Multivariate Time Series Anomaly Detection by Yeji Choi, Kwanghoon Sohn, Ig-Jae Kim

“…It allows the model to retain informative discrepancies that would otherwise be suppressed, thereby improving its ability to detect subtle anomalies. Second, we incorporate sparse self-attention with entropy-based regularization to capture essential inter-sensor relationships and suppress redundancy. …”
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Distributed Photovoltaic Communication Anomaly Detection Based on Spatiotemporal Feature Collaborative Modeling by Li Di, Zhuo Lv, Hao Chang, Junfei Cai

“…The temporal attention mechanism focuses on capturing subtle changes and trends in data sequences over time, ensuring a highly sensitive recognition of patterns inherent in time-series data. …”
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PPG-Based Accurate Insomnia Detection System Using Convolutional Neural Networks With Self-Attention Mechanism and Gated Recurrent Units by Hardik Telangore, Heneel Makwana, Prithviraj Verma, Manish Sharma, Hasan S. Mir, U. Rajendra Acharya

“…This study introduces a novel approach for PPG-based insomnia detection, utilizing Convolutional Neural Network (CNN) with self-attention, CNN with Gated Recurrent Unit (GRU), and transformer-based models. …”
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Optimized classification of potato leaf disease using EfficientNet-LITE and KE-SVM in diverse environments by Gopal Sangar, Velswamy Rajasekar

“…EfficientNet-LITE improves the model's emphasis on pertinent features through Channel Attention (CA) and 1-D Local Binary Pattern (LBP), while preserving computational economy with a reduced model size of 12.46 MB, fewer parameters at 3.11M, and a diminished FLOP count of 359.69 MFLOPs.ResultsBefore optimization, the SVM classifier attained an accuracy of 79.38% on uncontrolled data and 99.07% on laboratory-controlled data. …”
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Multi-label classification for image tamper detection based on Swin-T segmentation network in the spatial domain by Li Li, Kejia Zhang, Jianfeng Lu, Shanqing Zhang

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Vision Transformers for Image Classification: A Comparative Survey by Yaoli Wang, Yaojun Deng, Yuanjin Zheng, Pratik Chattopadhyay, Lipo Wang

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Rhinocerebral Mucormycosis in Patients with Diabetes Mellitus After a New Coronavirus Infection (COVID-19): СT and MRI Patterns Data by I. S. Gabdulganieva, N. R. Munirova, A. R. Zaripova, V. I. Anisimov

“…Objective: to study the computed tomography (CT) and magnetic resonance imaging (MRI) manifestations of rhinocerebral mucormycosis (RCM) in patients with diabetes mellitus and new coronavirus infection, to develop attentive attitude of radiologists for early detection of this pathology, rapid surgery and followup examinations.Material and methods. …”
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Urogenital schistosomiasis among school children in northwestern Tanzania: Prevalence, intensity of infection, associated factors, and pattern of urinary tract morbidities by Nyanda C. Justine, Titus R. Leeyio, Antje Fuss, Klaus Brehm, Humphrey D. Mazigo, Andreas Mueller

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Microbial Diversity, Co-Occurrence Patterns, and Functional Genes of Bacteria in Aged Coking Contaminated Soils by Polycyclic Aromatic Hydrocarbons: Implications to Soil Health and... by Liping Zheng, Yifan Yan, Qun Li, Junyang Du, Xiaosong Lu, Li Xu, Qunhui Xie, Yangsheng Chen, Aiguo Zhang, Bin Zhao

“…PAH contamination from coking plants have received widespread attention. However, the microbial diversity, co-occurrence patterns, and functional genes of bacteria in aged coking contaminated soils by PAHs are still not clear. …”
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Apnea detection using wrist actigraphy in patients with heterogeneous sleep disorders by Xiaoman Xing, Sizhi Ai, Jihui Zhang, Rui Huang, Yaping Liu, Dongming Quan, Jiacheng Ma, Guoli Wu, Jiangen Xu, Yuan Zhang, Hongliang Feng, Wen-fei Dong

“…We developed a novel approach combining apex-centric tokenization with a Multi-Head Causal Attention (MHCA) mechanism. Apex-centric tokenization enhances sensitivity to OSA events, while MHCA refines predictions and increases specificity in detecting oxygen desaturation. …”
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Depression detection using virtual avatar communication and eye tracking system by Ayumi Takemoto

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Temporal consistencies in two champion teams of European football? (¿Regularidades temporales en dos campeones del fútbol europeo?) by Miguel Pic Aguilar

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