Investigating and Optimizing MINDWALC Node Classification to Extract Interpretable Decision Trees from Knowledge Graphs by Maximilian Legnar, Joern-Helge Heinrich Siemoneit, Gilles Vandewiele, Jürgen Hesser, Zoran Popovic, Stefan Porubsky, Cleo-Aron Weis

“…This work deals with the investigation and optimization of the MINDWALC node classification algorithm with a focus on its ability to learn human-interpretable decision trees from knowledge graph databases. …”
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Indoor Multidimensional Reconstruction Based on Maximal Cliques by Yongtong Zhu, Lei Li, Na Liu, Qingdu Li, Ye Yuan

“…Applying deep learning models to obtain stereoscopic scene information, accompanied by algorithms such as target detection and semantic segmentation to obtain finer labels of things, is the dominant paradigm for robots. …”
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Orchard Navigation Method Based on RS-SC Loop Frame Search Method and SLAM Technology by Ning Xu, Qingshan Meng, Fengping Liu, Zhihe Li, Guangming Wang, Na Guo, Wenxuan Wu

“…In order to solve the problem that existing synchronous localization and map construction techniques are not accurate enough in this kind of environment, a loopback detection algorithm based on neighborhood search and scanning context fusion is proposed. …”
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Assessing distortion in carbon fiber woven fabrics based on machine vision by Shiyue Li, Quanzhou Yao, Lin Ye

“…A defect recognition method combining isometric and random feature sampling enables segmentation of abnormal fiber distribution regions through standard sample comparisons. …”
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Deep Residual Transfer Ensemble Model for mRNA Gene-Expression-Based Breast Cancer by Job Prasanth Kumar Chinta Kunta, Vijayalakshmi A. Lepakshi

“…Here, ResNet101 avoided gradient vanishing, while AlexNet provided 4096-dimensional features to train the ensemble-of-ensemble (E2E) classifier for consensus-based breast cancer detection. …”
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Electroencephalogram Based Emotion Recognition Using Hybrid Intelligent Method and Discrete Wavelet Transform by Duy Nguyen, Minh Tuan Nguyen, Kou Yamada

“…This paper proposes a novel algorithm for human emotion detection using a hybrid paradigm of convolutional neural networks and a boosting model. …”
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PCA-GWO-KELM Optimization Gait Recognition Indoor Fusion Localization Method by Xiaoyu Ji, Xiaoyue Xu, Suqing Yan, Jianming Xiao, Qiang Fu, Kamarul Hawari Bin Ghazali

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Forest Change Monitoring Based on Block Instance Sampling and Homomorphic Hypothesis Margin Evaluation by Wei Feng, Fan Bu, Puxia Wu, Gabriel Dauphin, Yinghui Quan, Mengdao Xing

“…The former can not only assess the confidence level of each pixel category but also make regional boundaries clearer, and the latter can replace the test set so that all samples can be used for change detection. The experimental results show that the OOB accuracy obtained by spatial features with whole block sampling was <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>7.2</mn><mo>%</mo></mrow></semantics></math></inline-formula> higher than that obtained by spectral features with pixel-based sampling and 2–3% higher than that for block center sampling, of which the highest value reached <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>98.8</mn><mo>%</mo></mrow></semantics></math></inline-formula>. …”
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Advanced machine learning techniques reveal multidimensional EEG abnormalities in children with ADHD: a framework for automatic diagnosis by Ying Mao, Ying Mao, Xuchen Qi, Xuchen Qi, Xuchen Qi, Lingyan He, Shan Wang, Zhaowei Wang, Fang Wang, Fang Wang

“…Then, four widely-employed machine learning algorithms (including random forest (RF), XGBoost, CatBoost, and LightGBM) were used for classification calculations, and the SHAP algorithm was then used to assess the importance of the contributing features to interpret the model’s decision process.ResultsThe results showed that the highest classification accuracy of 99.58% for pediatric ADHD detection was obtained with the CatBoost model based on the optimal feature subset of 206 features (PSD/FuzEn/MI = 53/5/148). …”
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Enhanced Fault Localization in Multi-Terminal HVDC Systems Using Improved Gaussian Process Regression by Abha Pragati, Manohar Mishra, Pritam Bhowmik, Josep M. Guerrero, Debadatta Amaresh Gadanayak

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When Two are Better Than One: Synthesizing Heavily Unbalanced Data by Francisco Ferreira, Nuno Lourenco, Bruno Cabral, Joao Paulo Fernandes

“…., privacy (strictly) needs to be respected when using or sharing data, thus protecting both the interests of users and organizations. Fraud Detection systems are examples of such systems where Machine Learning algorithms leverage information to classify financial transactions as legitimate or illicit. …”
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Intelligent prediction method for fire temperature fields in underground exhibition spaces of high-intensity urban areas by Yuan Shi, Yang Zhou, Guanhua Qu, Lan Wang, Rong Wang, Zenghui Liu

“…Through a comparative selection of multiple algorithms, it was found that the RF prediction model with 41 input features performs best in terms of accuracy and applicability, with the Mean Absolute Errors (MAE) values of 1.09 °C and 0.52 °C for fire rooms and no-fire rooms, respectively, and the Mean Absolute Percentage Errors (MAPE) values of 1.11 % and 0.68 %, respectively. …”
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Lightweight defocus deblurring network for curved-tunnel line scanning using wide-angle lenses by Shaojie Qin, Taiyue Qi, Xiaodong Huang, Xiao Liang

“…Additionally, the proposed feature refinement block captures the structurally similar features to enhance the image details, increasing the peak signal-to-noise ratio (PSNR). …”
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Iterative segmentation and classification for enhanced crop disease diagnosis using optimized hybrid U-Nets model by Malathi Chilakalapudi, Sheela Jayachandran

“…Along with this is the use of a Fuzzy U-Net++ model for image segmentation, whereby fuzzy decisions in generously instill an increase in performance for image segmentation. Feature selection itself is innovated by the introduction of the Moving Gorilla Remora Algorithm (MGRA) combined with convolutional operations, setting a new benchmark in the selection of optimal features pertaining to disease identification operations. …”
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Accurate recognition of UAVs on multi-scenario perception with YOLOv9-CAG by Jincan Zhu, Jian Rong, Weili Kou, Qingyang Zhou, Peichun Suo

“…This algorithm integrates the detection capabilities of visible light, infrared, and audio signals. …”
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Bridging the Gap Between Computational Efficiency and Segmentation Fidelity in Object-Based Image Analysis by Fernanda Pereira Leite Aguiar, Irenilza de Alencar Nääs, Marcelo Tsuguio Okano

“…A critical issue in image analysis for analyzing animal behavior is accurate object detection and tracking in dynamic and complex environments. …”
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Establishment and Application of Wireless Fingerprint Library for Urban Rail Transit Vehicle-wayside Communication by WU Jie

“…The library utilizes the DeepFS algorithm, enabling adaptive updates of the wireless feature data for each grid. …”
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Evaluation criteria of centralization options in the architecture of multicomputer systems with traps and baits by Antonina Kashtalian, Sergii Lysenko, Anatoliy Sachenko, Bohdan Savenko, Oleg Savenko, Andrii Nicheporuk

“…New mathematical models were developed for the criteria for operational efficiency, stability, integrity and security in relation to the system center, which, unlike the known mathematical models for evaluating system centers for selecting the next options for centralization, are presented in analytical expressions that take into account the features of the types of centralization in the system architecture, indicators of operational efficiency, stability, integrity and security in relation to the system center and allow forming on their basis an objective function for evaluating options for centralization in systems, the feature of which is the hiding of components with the system center from detection by attackers. …”
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Joint simplification of various types spatial objects while preserving topological relationships by Olga P. Yakimova, Dmitriy M. Murin, Vladislav G. Gorshkov

“…The first step of the algorithm is the construction of a special mesh data structure. …”
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xAAD&#x2013;Post-Feedback Explainability for Active Anomaly Discovery by Damir Kopljar, Vjekoslav Drvar, Jurica Babic, Vedran Podobnik

“…Anomaly detection algorithms are widely used across various domains, but they often suffer from high false positive rates and lack of interpretability. …”
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