Privacy protection risk identification mechanism based on automated feature combination by CAI Minchao, YAO Hongwei, WANG Yang, QIN Zhan, CHEN Shaomeng, REN Kui

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Efficient Training Data Generation for Reduced-Order Modeling in a Transonic Flight Regime by Haojie Liu, Yonghui Zhao

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YOLO-SMUG: An Efficient and Lightweight Infrared Object Detection Model for Unmanned Aerial Vehicles by Xinzhe Luo, Xiaogang Zhu

“…To tackle the high computational demands and accuracy limitations in UAV-based infrared object detection, this study proposes YOLO-SMUG, a lightweight detection algorithm optimized for small object identification. The model incorporates an enhanced backbone architecture that integrates the lightweight Shuffle_Block algorithm and the Multi-Scale Dilated Attention (MSDA) mechanism, enabling effective small object feature extraction while significantly reducing parameter size and computational cost without compromising detection accuracy. …”
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Hyperspectral Image-Based Identification of Maritime Objects Using Convolutional Neural Networks and Classifier Models by Dongmin Seo, Daekyeom Lee, Sekil Park, Sangwoo Oh

“…The identification of maritime objects is crucial for ensuring navigational safety, enabling effective environmental monitoring, and facilitating efficient maritime search and rescue operations. …”
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Plastic Injection Molding Process Analysis: Data Integration and Modeling for Improved Production Efficiency by Jose Isidro Hernández-Vega, Luis Alejandro Reynoso-Guajardo, Mario Carlos Gallardo-Morales, María Ernestina Macias-Arias, Amadeo Hernández, Nain de la Cruz, Jesús E. Soto-Soto, Carlos Hernández-Santos

“…These results provide a strong foundation for the early identification of potential problems and informed decision making to improve the efficiency of the plastic injection molding process. …”
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Chemical Safety Risk Identification and Analysis Based on Improved LDA Topic Model and Bayesian Networks by Zhiyong Zhou, Jiahang Guo, Jianhui Huang

“…Therefore, this dissertation researches chemical safety risk factor identification and analysis predicated on improved LDA topic model and Bayesian network. …”
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Identification of maneuvering models for wind-assisted ships with large rudders using virtual captive tests by Martin Alexandersson, Wengang Mao, Jonas W. Ringsberg, Martin Kjellberg

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Frequency-Based Cable Tension Identification Using a Nonlinear Model with Complex Boundary Constraints by Wen-ming Zhang, Zhi-wei Wang

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Deep Learning-Based Classification of Macrofungi: Comparative Analysis of Advanced Models for Accurate Fungi Identification by Sifa Ozsari, Eda Kumru, Fatih Ekinci, Ilgaz Akata, Mehmet Serdar Guzel, Koray Acici, Eray Ozcan, Tunc Asuroglu

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Automatic Identification Model for Landslide Disaster Using Remote Sensing Images Based on Improved Multiresunet by Zhenyu Zhao, Shucheng Tan, Qinghua Zhang, Hui Chen

“…To address this problem, a novel automatic landslide hazard remote sensing image identification model, MultiResUNet-BFDC, is proposed. …”
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AI-Powered Identification of Osteoporosis in Dental Panoramic Radiographs: Addressing Methodological Flaws in Current Research by Robert Gaudin, Shankeeth Vinayahalingam, Niels van Nistelrooij, Iman Ghanad, Wolfus Otto, Stephan Kewenig, Carsten Rendenbach, Vasilios Alevizakos, Pascal Grün, Florian Kofler, Max Heiland, Constantin von See

“…Subsequently, the predicted regions of interest were extracted from the PRs and processed by the EfficientNet classification model. <b>Results:</b> The model for osteoporosis detection on a PR achieved an overall sensitivity of 0.83 and an F1-score of 0.53. …”
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Identification of maize kernel varieties based on interpretable ensemble algorithms by Chunguang Bi, Chunguang Bi, Xinhua Bi, Jinjing Liu, Hao Xie, Shuo Zhang, He Chen, Mohan Wang, Lei Shi, Lei Shi, Shaozhong Song

“…Shapley Additive exPlanation was applied for interpretable ensemble learning.ResultsThe HDE-Stacking identification model achieved 97.78% accuracy. The spectral bands at 784 nm, 910 nm, 732 nm, 962 nm, and 666 nm showed positive impacts on identification results.DiscussionThis research provides a scientific basis for efficient identification of different corn kernel varieties, enhancing accuracy and traceability in germplasm resource management. …”
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Automated Breast Cancer Detection in Mammograms using Transfer Learningbased Deep Learning Models by Preeti Katiyar, Krishna Singh

“…The initial MIAS dataset underwent several preprocessing techniques, including noise reduction, breast image contrast enhancement, non breast region deletion and malignant lesion identification, before analysis. An intricately designed fully connected classifier complements pretrained Convolutional Neural Network (CNN) architectures like ResNet50 and VGG16 in the proposed model. …”
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A hybrid filtering and deep learning approach for early Alzheimer’s disease identification by Md. Khabir Uddin Ahamed, Rakib Hossen, Bikash Kumar Paul, Mohammad Hasan, Waled Hussein Al-Arashi, Mohsin Kazi, Md. Alamin Talukder

“…Furthermore, the deep learning model used in this study is constructed on the EfficientNetV2B3 architecture, augmented with additional layers and fine-tuning to guarantee effective classification among four categories: Mild, moderate, very mild, and non-demented. …”
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Fuzzy rank fusion of deep neural networks for weed identification in groundnut crop by Akshay Dheeraj, Rajnish Kumar Chaturvedi, Sapna Nigam, Md. Ashraful Haque, Sudeep Marwaha

“…Base models EfficientNetV2B0 and DenseNet121 have achieved the classification accuracy of 98.66 ± 0.39 and 98.92 ± 0.19 respectively. …”
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Exploring Core Knowledge in Interdisciplinary Research: Insights from Topic Modeling Analysis by Shuangyan Wu, Mixin Lin, Mengxiao Ji, Ting Wang

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Model and Method of Solid Household Waste Sorting for Their Effective Thermal Disposal by Hanna Lysiuk, Oksana Maksymova

“…The work considers the development of a simulation model and an automated method of sorting solid household waste based on the identification of a portion of the studied raw material with further classification according to accepted groups of characteristic chemical composition. …”
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Pollution source identification methods and remediation technologies of groundwater: A review by Ya-ci Liu, Yu-hong Fei, Ya-song Li, Xi-lin Bao, Peng-wei Zhang

“…The methods for identifying pollution sources mainly include geophysical exploration, geochemistry, isotopic tracing, and numerical modeling. Among these identification methods, only the numerical modeling can recognize various information on pollution sources, while other methods can only identify a certain aspect of pollution sources. …”
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Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization Algorithms by Dhiaa Halboot Muhsen, Haider Tarish Haider, Yaarob Al-Nidawi

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Low pressure PEM electrolyzer system modeling with heat loss representation by Asmaa A. Ghany, Mohamed Mahmoud Samy

“…MATLAB programming is used to develop the model and evaluate the accuracy of the proposed identification method.…”
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