LHB-YOLOv8: An Optimized YOLOv8 Network for Complex Background Drop Stone Detection by Anjun Yu, Hongrui Fan, Yonghua Xiong, Longsheng Wei, Jinhua She

“…In this paper, we propose an enhanced high-speed slope rockfall detection method based on YOLOv8n. First, the LSKAttention mechanism is added to the backbone part to improve the model’s ability to balance the processing of global and local information, which enhances the model’s accuracy and generalization ability. …”
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Federated Learning With Sailfish-Optimized Ensemble Models for Anomaly Detection in IoT Edge Computing Environment by Aravam Babu, A. Bagubali

“…Additionally, the framework is evaluated against leading FL-based and traditional anomaly detection models, including Local Outlier Factor (LOF), Generative Adversaria (GAN), and Variational autoencoder (VAE), demonstrating superior performance in recall and F1-score. …”
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LT-YOLO: long-term temporal enhanced YOLO for stenosis detection on invasive coronary angiography by Jiaxin Li, Xiang Tang, Xuesong Wang

“…Our approach integrates long-term temporal information and spatial information for stenosis detection with state-space models and YOLOv8. First, a spatial-aware backbone based on a dynamic Transformer and C2f Convolution of YOLOv8 combines the local and global feature extraction to distinguish the coronary regions from the background. …”
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Explainable CNN for brain tumor detection and classification through XAI based key features identification by Shagufta Iftikhar, Nadeem Anjum, Abdul Basit Siddiqui, Masood Ur Rehman, Naeem Ramzan

“…The major contribution of this paper is ensuring that the model focuses on the most relevant features for tumor detection and classification, while simultaneously reducing complexity, by minimizing the number of layers. …”
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Exposed conductor detection of 10 kV distribution line based on improved YOLOv8 by Qiwen JING, Sipeng HAO, Siyuan LI

“…Traditional manual inspection methods often fail to detect such defects in a timely manner. A detection method for exposed conductors in 10 kV distribution lines is proposd based on an improved YOLOv8 algorithm,which is designed to assist power grid maintenance personnel detecting conductor exposed defects quickly and efficiently. …”
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A Novel Ensemble of Deep Learning Approach for Cybersecurity Intrusion Detection with Explainable Artificial Intelligence by Abdullah Alabdulatif

“…The proposed model combines an Artificial Neural Network and Support Vector Machine as base classifiers and employs a Random Forest as a meta-classifier to fuse predictions, improving detection performance. Recursive Feature Elimination is utilized for optimal feature selection, while SHapley Additive exPlanations (SHAP) provide both global and local interpretability of the model’s decisions. …”
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Real-Time Explainable Multiclass Object Detection for Quality Assessment in 2-Dimensional Radiography Images by Sadra Naddaf-Sh, M-Mahdi Naddaf-Sh, Hassan Zargarzadeh, Maxim Dalton, Soodabeh Ramezani, Gabriel Elpers, Vinay S. Baburao, Amir R. Kashani

“…The models are evaluated and compared against each other, various critical hyperparameters and components are optimized, and local explainability of models is discussed. Additionally, AutoAugment for object detection and various techniques are utilized and investigated. …”
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PS-GCN: psycholinguistic graph and sentiment semantic fused graph convolutional networks for personality detection by Wenjuan Liu, Zhengyan Sun, Subo Wei, Shunxiang Zhang, Guangli Zhu, Lei Chen

“…Firstly, the Bi-LSTM network captures local features of preprocessed sentences to accurately represent the output of sentence sentiment features. …”
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Improving Circulating Tumor Cell Detection Using Image Synthesis and Transformer Models in Cancer Diagnostics by Shuang Liang, Xue Bai, Yu Gu

“…This study proposes a data generation method using the Segment Anything Model (SAM) combined with a copy–paste strategy. We develop a detection network based on the Swin Transformer, featuring a backbone network, scale adapter module, shape adapter module, and detection head, which enhances CTC localization and identification in images. …”
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BEVCorner: Enhancing Bird’s-Eye View Object Detection with Monocular Features via Depth Fusion by Jesslyn Nathania, Qiyuan Liu, Zhiheng Li, Liming Liu, Yipeng Gao

“…This research paper presents BEVCorner, a novel framework that synergistically integrates monocular and multi-view pipelines for enhanced 3D object detection in autonomous driving. By fusing depth maps from Bird’s-Eye View (BEV) with object-centric depth estimates from monocular detection, BEVCorner enhances both global context and local precision, addressing the limitations of existing methods in depth precision, occlusion robustness, and computational efficiency. …”
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Weight-Based Clustering Decision Fusion Algorithm for Distributed Target Detection in Wireless Sensor Networks by Haiping Huang, Lei Chen, Xiao Cao, Ruchuan Wang, Qianyi Wang

“…Each local sensor detects the target signal in the region of interests and collects relevant data, and then it sends the respective data to the data fusion center (DFC) for aggregation processing and judgment making whether the target signal exists or not. …”
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Automated detection of weld defects in TOFD images for steel bridges using generative adversarial networks by Yanfeng Gong, Zihao Chen, Hong Zhang, Meng Xu, Wen Deng

“…Time-of-flight diffraction (TOFD) has been widely adopted for weld defect detection in bridge steel quality assurance due to its harmlessness to the human body, real-time performance, and satisfactory detection accuracy. …”
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XAI-XGBoost: an innovative explainable intrusion detection approach for securing internet of medical things systems by Yousif Hosain, Muhammet Çakmak

“…Explainable AI techniques, namely SHAP and LIME, are employed to provide global and local insights into model predictions, enhancing interpretability and trustworthiness. …”
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Improved model MASW YOLO for small target detection in UAV images based on YOLOv8 by Xianghe Meng, Fei Yuan, Dexiang Zhang

“…The backbone network structure is enhanced by incorporating a multi-scale convolutional MSCA attention mechanism, which introduces a deep convolution process to aggregate local information. This method aims to increase small-target detection accuracy. …”
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Detection, Characterization, and Molecular Typing of Human Mycoplasma spp. from Major Hospitals in Cairo, Egypt by Mirihan A. Metwally, Aymen S. Yassin, Tamer M. Essam, Hayam M. Hamouda, Magdy A. Amin

“…Molecular techniques were found to be of more rapid, highly sensitive, able to detect nonviable organisms, and cost effective. These results shed light on difficulties of Mycoplasma detection and the superiority of molecular techniques over culture.…”
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Detecting behavioural changes in human movement to inform the spatial scale of interventions against COVID-19. by Hamish Gibbs, Emily Nightingale, Yang Liu, James Cheshire, Leon Danon, Liam Smeeth, Carl A B Pearson, Chris Grundy, LSHTM CMMID COVID-19 working group, Adam J Kucharski, Rosalind M Eggo

“…We use detailed human mobility data aggregated from Facebook users to determine how the spatially-explicit network of movements changed before and during the lockdown period, in response to the easing of restrictions, and to the introduction of locally-targeted interventions. We also apply community detection techniques to the weighted, directed network of movements to identify geographically-explicit movement communities and measure the evolution of these community structures through time. …”
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Interpersonal Relationship Detection Using Multi-Head Graph Attention Networks With Multi-Feature Fusion by Simge Akay, Duygu Cakir, Nafiz Arica

“…This paper presents a novel Multi-Head Graph Attention Network (MHF-GAT) with Multi-Feature Fusion for interpersonal relationship detection (IRD) from images. The proposed architecture decomposes heterogeneous visual and semantic features into three specialized modules: local features capturing direct interpersonal cues (e.g., age differences, expression similarity), contextual features modeling environmental information (e.g., scene, objects), and semantic features derived from image captions. …”
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Retrospective analysis of ultrasound criteria for newly diagnosed extragenital endometriosis detected during preventive examinations by O. E. Nechaeva, I. S. Gruzdev, Yu. V. Popov, A. G. Kedrova, V. N. Lesnyak, N. S. Nosenko

“…Despite the ability to demonstrate infiltrative growth and tendency to local recurrence and invasion, endometriosis is considered as a benign proliferative disease. …”
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FEVT-SAR: Multicategory Oriented SAR Ship Detection Based on Feature Enhancement Vision Transformer by Minding Fang, Yu Gu, Dongliang Peng

“…Issues such as complex noise interference and the long-tail distribution of data present many challenges to the multicategory ship detection task in synthetic aperture radar (SAR) images. …”
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Anomaly detection and confidence interval‐based replacement in decay state coefficient of ship power system by Xingshan Chang, Xinping Yan, Bohua Qiu, Muheng Wei, Jie Liu, Hanhua Zhu

“…The model calculates three local statistical measures within each sliding window and employs the Z‐score method for anomaly detection. …”
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