MHFS-FORMER: Multiple-Scale Hybrid Features Transformer for Lane Detection by Dongqi Yan, Tao Zhang

“…Furthermore, a significant drawback of most existing lane-detection algorithms lies in their reliance on complex post-processing and strong prior knowledge. …”
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Using video for reconstruction in SfM. The Capo d’Omo Tower on Mount Argentario by Fabio Lanfranchi, Piero Barlozzini, Luca Martelli

“…Even more widespread are so-called unmanned aircraft systems (UAS), inoffensive and lighter than 250 g, due to the simplification of the related standards and continued improvements in their acquisition devices. The most advanced photo-modelling programs are now able to process video clips directly, automatically selecting the photos suitable for input in scale-invariant feature transform (SIFT) and speeded up robust features (SURF) algorithms, essential aspects of structure from motion (SfM). …”
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An AI framework for counterattack detection and decision-making evaluation in football by Jiangyan Yang, Huanmin Ge, Yixiong Cui

“…The findings of this study can offer strategic insights for coaching and gameplay improvement.…”
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An autonomous navigation method for field phenotyping robot based on ground-air collaboration by Zikang Zhang, Zhengda Li, Meng Yang, Jiale Cui, Yang Shao, Youchun Ding, Wanneng Yang, Wen Qiao, Peng Song

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Leveraging Multilingual Transformer for Multiclass Sentiment Analysis in Code-Mixed Data of Low-Resource Languages by Muhammad Kashif Nazir, Cm Nadeem Faisal, Muhammad Asif Habib, Haseeb Ahmad

“…Additionally, the proposed model outperformed other transformer-based models, as well as deep learning and machine learning algorithms in sentiment extraction from code-mixed data. …”
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A critical review on the applications of Sentinel satellite datasets for soil moisture assessment in crop production by Anela Mkhwenkwana, Trylee Nyasha Matongera, Ciara Blaauw, Onisimo Mutanga

“…Further development of robust retrieval models that incorporate topography, soil roughness, and texture are essential for improving soil moisture accuracy in diverse agricultural landscapes. …”
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Measures of state support for increasing labor productivity: synchronization of state goals, interests and business opportunities by R. V. Plyusov, N. A. Bogdanova, O. L. Mitryakova, V. A. Umnov

“…This article discusses the possibilities of synchronizing the goals of state support for improving labor productivity with the real interests of business in solving the problems of effective use of human resources. …”
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Enhancing stone matrix asphalt performance with sugarcane bagasse ash: Mechanical properties and machine learning-based predictions using XGBoost and random forest by Hamed Khani Sanij, Rezvan Babagoli, Reza Mohammadi Elyasi

“…These improvements are attributed to the high silica content and pozzolanic nature of SCBA, which contributed to better bonding and matrix densification. …”
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Current Topics on the Integration of Artificial Intelligence in the Histopathological and Molecular Diagnosis of Uveal Melanoma by Serena Salzano, Giuseppe Broggi, Andrea Russo, Teresio Avitabile, Antonio Longo, Rosario Caltabiano, Manuel Mazzucchelli

“…<b>Conclusions:</b> Despite these promising developments, this review acknowledges existing hurdles to AI implementation, including issues with data standardization and the interpretability of AI models. It emphasizes the need for further research to fully integrate AI into clinical workflows, ultimately aiming to improve patient care and outcomes.…”
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The Impact of a Deep Learning Self-Adaptive Colour Restoration Pipeline for Deep Underwater Images in 3D Reconstruction by M. Vlachos, D. Skarlatos, S. Demesticha

“…The proposed approach leverages deep learning to correct colour distortions without relying on physical models of underwater light propagation. Evaluation was performed using established feature detection algorithms, such as SIFT and SURF, applied to multiple underwater datasets capturing diverse imaging conditions. …”
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Scientific Machine Learning for Elastic and Acoustic Wave Propagation: Neural Operator and Physics-Guided Neural Network by Nafisa Mehtaj, Sourav Banerjee

“…Through comparative analysis of existing NO algorithms applied across different engineering fields, this study demonstrates how NOs improve generalization, accelerate inference, and enhance scalability for practical wave modeling scenarios. …”
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Machine learning-based prediction of physical parameters in heterogeneous carbonate reservoirs using well log data by Fuyong Wang, Xianmu Hou

“…Machine learning models are trained and evaluated to predict carbonate rock properties. …”
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Predictive analysis of heart disease using quantum-assisted machine learning by Mehroush Banday, Sherin Zafar, Parul Agarwal, M. Afshar Alam, Siddhartha Sankar Biswas, Imran Hussain, K. M. Abubeker

“…Abstract Coronary heart disease (CHD) is a severe cardiac disease, and hence, its early diagnosis is essential as it improves treatment results and saves money on medical care. …”
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Incidence and Predictors of Acute Kidney Injury Following Advanced Ovarian Cancer Cytoreduction at a Tertiary UK Centre: An Exploratory Analysis and Insights from Explainable Artif... by Elizabeth Ratcliffe, Ciara Devlin, Sarika Munot, Timothy Broadhead, Amudha Thangavelu, Michela Quaranta, David Nugent, Evangelos Kalampokis, Diederick De Jong, Alexandros Laios

“…AKI is linked to heightened surgical risk-taking, underscoring the need for improved guidelines focusing on postoperative monitoring for targeted patients. …”
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Deep Learning Network Selection and Optimized Information Fusion for Enhanced COVID-19 Detection: A Literature Review by Olga Adriana Caliman Sturdza, Florin Filip, Monica Terteliu Baitan, Mihai Dimian

“…Individual ResNet architectures, along with CNN models, demonstrate strong diagnostic performance through the transfer protocol; however, ViTs provide better performance, with improved readability and reduced data requirements. …”
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Wearing WHOOP More Frequently Is Associated with Better Biometrics and Healthier Sleep and Activity Patterns by Gregory J. Grosicki, Finnbarr Fielding, Jeongeun Kim, Christopher J. Chapman, Maria Olaru, William von Hippel, Kristen E. Holmes

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Spectral Variation and Corresponding Changing Mechanism of Suspended Particulate Material Absorption in Poyang Lake during Flood Periods by Yuandong Wang, Xibin You, Lianfang Yu, Lihong Meng, Xiangming Xu, Guangxu Liu

“…Evidence also presented that the nonlinear dependency of specific phytoplankton particulate absorption on pigment concentration for various trophic statuses in different periods could be unstable due to relative contributions of the package effect and accessory pigments; this could bring uncertainties to the parameterization of optical models and remote sensing algorithms proposed for accurate applications in lake water environment monitoring.…”
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Detection of Right and Left Ventricular Dysfunction in Pediatric Patients Using Artificial Intelligence–Enabled ECGs by Scott Anjewierden, Donnchadh O'Sullivan, Kathryn E. Mangold, Grace Greason, Itzhak Zachi Attia, Francisco Lopez‐Jimenez, Paul A. Friedman, Samuel J. Asirvatham, Jason Anderson, Benjamin W. Eidem, Jonathan N. Johnson, Shisheer Havangi Prakash, Talha Niaz, Malini Madhavan

“…Conclusions An artificial intelligence–enabled ECG demonstrates accurate detection of both LVSD and RVSD in pediatric patients. While adult‐trained models offer good performance, improvements are seen when training pediatric‐specific models.…”
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Machine learning-based integration develops relapse related signature for predicting prognosis and indicating immune microenvironment infiltration in breast cancer by Junyi Li, Shixin Li, Dongpo Zhang, Yibing Zhu, Yue Wang, Xiaoxiao Xing, Juefei Mo, Yong Zhang, Daixiang Liao, Jun Li

“…To address these limitations, this study systematically analyzed RNA-seq high-throughput data and combined 10 machine learning algorithms to construct 117 models. The optimal algorithm combination, StepCox[both] and ridge regression, was identified, and an immune-related gene signature (IRGS) composed of 12 genes was developed. …”
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State-of-the-art review on Automatic Vertical Drilling Tools: Addressing vibrational load challenges in oil and gas operations by Jialin Tian, Ameer Dheyaa

“…Frameworks for addressing these gaps are proposed, emphasizing the need for advanced computational techniques, including simulation-driven design, smart control algorithms, and innovative material applications. Recommendations for future research highlight strategies to extend tool life, improve drilling accuracy, and minimize environmental impact. …”
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