DualCMNet: a lightweight dual-branch network for maize variety identification based on multi-modal feature fusion by Xinhua Bi, Hao Xie, Ziyi Song, Jinge Li, Chang Liu, Xiaozhu Zhou, Helong Yu, Chunguang Bi, Ming Zhao

“…This study not only provides an accurate and efficient solution for maize seed variety identification but also establishes a universal framework that can be extended to variety classification tasks of other crops.…”
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Gas Leak Detection and Leakage Rate Identification in Underground Utility Tunnels Using a Convolutional Recurrent Neural Network by Ziyang Jiang, Canghai Zhang, Zhao Xu, Wenbin Song

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ANN-SVM-IP: An Innovative Method for Rapidly and Efficiently Detecting and Classifying of External Defects of Apple Fruits by Nashaat M. Hussain Hassan, Mohamed M. Hassan Mahmoud, Mohamed A. Ismeil, M. Mourad Mabrook, A. A. Donkol, A. M. Mabrouk

“…The proposed model focuses on speed and scalability by relying on the combination of traditional machine learning techniques, which are characterized by low cost, high performance, and simplicity of implementation, which was confirmed by the results obtained (99.4% for separating different defects, 97% for defect extraction, and a speed of 3.29 milliseconds, sufficient to complete defect identification and classification for each frame). …”
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Corn Seed Freezing Damage Identification of Different Sides Based on Hyperspectral Imaging and SPA-2DCOS Fusion Algorithm by Jun Zhang, Limin Dai, Ruiyuan Zhuang

“…In the endosperm side’s freezing damage identification, the SNV+SVM model obtained the highest accuracies of 92.9% and 90.0% with the training set and testing set, based on the full-waveband data. …”
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Implementation of Efficient Artificial Neural Network Data Fusion Classification Technique for Induction Motor Fault Detection by Altaf S., Mehmood M. S., Imran M.

“…In this study single sensor method is applied for fault diagnosis depending on identification of single parameter. At early stages it is hard to diagnose machine fault due to ambiguities in modeling environment. …”
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Construction of TRIF-knockout NA and BHK-21 cell lines and effect on rabies virus proliferation efficiency by Weitao HUANG, Jiaqi LI, Yao PENG, Xiangping YIN, Xiaofeng GUO, Jun LUO

“…The findings not only provide substantial support for further investigation of TRIF function, but also establish novel cellular models for RABV cultivation and research.…”
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Identification and Prioritizing Critical Success Factors for HR Shared Services Implementation in Multi-Business Firms Using DEMATEL Method by Fatemeh Goudarzi Hossainabadi, Mohammad Reza Akhavan Anvari, Kamyar Raissifar

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Genome-Wide-Association-Analysis-Based Identification of Genetic Loci and Candidate Genes Associated with Cold Germination in Sweet Corn by Changjin Wang, Yulin Yu, Jie Liu, Ahmad Rizwan, Zain Abbas, Haibing Yu, Xinxin Cheng

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Opportunities, challenges and future perspectives of using bioinformatics and artificial intelligence techniques on tropical disease identification using omics data by S. M. Vidanagamachchi, K. M. G. T. R. Waidyarathna

“…Several AI-assisted models including XAI can be used to identify diseases and repurpose therapeutic targets and biomarkers efficiently. …”
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Development of a Baby Cry Identification System Using a Raspberry Pi-Based Embedded System and Machine Learning by Mohcin Mekhfioui, Wiam Fadel, Fatima Ezzahra Hammouch, Oussama Laayati, Marouan Bouchouirbat, Nabil El Bazi, Amal Satif, Tarik Boujiha, Ahmed Chebak

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Identification and Evaluation of the Main Constraints on Cotton Production Within a Collective Drip Irrigation System in Southern Xinjiang, China by Zhanghao Sun, Zhen Wang, Jiusheng Li

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MSThunder: A deep learning-based nontargeted analytical framework for the accurate and rapid identification of unknown organic pollutants in water by Quanzhen Liu, Pan Chen, Qingwei Bu, Yize Sun, Zhengchao Chen, Xiong Xu, Donghong Wang

“…Then, we established a transformer model that transitions from formulas to structural sequences, less constrained by the lack of training data. …”
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Identification and Characterization of Lipid Droplet-Associated Protein (LDAP) Isoforms from Tung Tree (<i>Vernicia fordii</i>) by Alyssa C. Clews, Payton S. Whitehead, Lingling Zhang, Shiyou Lü, Jay M. Shockey, Kent D. Chapman, John M. Dyer, Yang Xu, Robert T. Mullen

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Provable security EPC information service communication scheme for EPC network by Jing-feng LI, Heng PAN, Wei-feng GUO

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CBLN-YOLO: An Improved YOLO11n-Seg Network for Cotton Topping in Fields by Yufei Xie, Liping Chen

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MÉTODOS PARA IDENTIFICACIÓN DE PELIGROS, ANÁLISIS, EVALUACIÓN Y TRATAMIENTO DE LOS RIESGOS EN COLOMBIA by CARLOS ALIRIO BELTRÁN RODRÍGUEZ, JAIME ALEXANDER MURCIA PAMPLONA

“…This article presents an overview of some models of hazard identification, analysis, evaluation and treatment of risks especially in the workplace, as part of the methodologies of integrated risk management as one of its main components. …”
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Melanoma risk prediction models by Nikolić Jelena, Lončar-Turukalo Tatjana, Sladojević Srđan, Marinković Marija, Janjić Zlata

“…The aim of this study was to identify most significant factors for melanoma prediction in our population and to create prognostic models for identification and differentiation of individuals at risk. …”
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DeepSafe:Two-level deep learning approach for disaster victims detection by Amir Azizi, Panayiotis Charalambous, Yiorgos Chrysanthou

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Identification of ATF-7 and the insulin signaling pathway in the regulation of metallothionein in C. elegans suggests roles in aging and reactive oxygen species. by Julie A Hall, Matthew K McElwee, Jonathan H Freedman

“…The insulin signaling pathway is known to influence the aging process; however, various factors responsible for affecting the aging phenotype are unknown. Identification of portions of the insulin signaling pathway as regulators of metallothionein expression supports the hypothesis that longevity is affected by the expression of this efficient ROS scavenger.…”
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Deep Residual Network With Integrated StarDist Nuclei Segmentation for Papillary Thyroid Cancer Identification: A Pathologist-Inspired Approach by Nabila Husna Shabrina, Dadang Gunawan, Mia Rizkinia, Agnes Stephanie Harahap, Mohammad Ikhsan, Rifai Chai, Maria Francisca Ham

“…Our findings confirmed that incorporating nuclei segmentation significantly enhances classification performance and model interpretability. The proposed model enhances feature localization by integrating nucleus segmentation with Deep Residual Networks, yielding a practical and efficient solution for histopathological PTC analysis.…”
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