Integrated pixel-level crack detection and quantification using an ensemble of advanced U-Net architectures by Rakshitha R, Srinath S, N Vinay Kumar, Rashmi S, Poornima B V

“…Binary Focal Loss proved particularly effective in addressing class imbalance across four benchmark datasets. To further improve segmentation performance, two ensemble strategies were applied: stochastic reordering using logical operations (AND, OR, and averaging) and a weighted average ensemble optimized through grid search. …”
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Lightweight image super-resolution network based on muti-domain information enhancement by KOU Qiqi, LIU Gui, JIANG He, CHEN Liangliang, CHENG Deqiang

“…By processing information across different feature domains, both global and local low-frequency and high-frequency features were optimized, significantly improving the model’s performance in detail recovery and image reconstruction. …”
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Training a Minesweeper Agent Using a Convolutional Neural Network by Wenbo Wang, Chengyou Lei

“…Although there is room for improvement in sample efficiency and training stability in the DQN model, its greater generalization ability makes it highly promising for application in more complex decision-making tasks.…”
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Predicting anemia management in dialysis patients using open-source machine learning libraries by Takahiro Inoue, Norio Hanafusa, Yuki Kawaguchi, Ken Tsuchiya

“…Performance metrics were compared across models, including XGBoost and LightGBM, to identify the most accurate algorithms. …”
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Securing fruit trees future: AI-driven early warning and predictive systems for abiotic stress in changing climate by Muhammad Ahtasham Mushtaq, Muhammad Ateeq, Muhammad Ikram, Shariq Mahmood Alam, Muhammad Mohsin Kaleem, Muhammad Atiq Ashraf, Muhammad Asim, Khalid F. Almutairi, Mahmoud F. Seleiman, Fareeha Shireen

“…AI integrated approaches such as stress prediction, irrigation optimization, and image-based phenotyping have enhanced agriculture, while machine learning models like Random Forest and Gradient Boosting improve stress management. …”
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Automated segmentation of brain metastases in T1-weighted contrast-enhanced MR images pre and post stereotactic radiosurgery by Hemalatha Kanakarajan, Wouter De Baene, Patrick Hanssens, Margriet Sitskoorn

“…Abstract Background and purpose Accurate segmentation of brain metastases on Magnetic Resonance Imaging (MRI) is tedious and time-consuming for radiologists that could be optimized with deep learning (DL). Previous studies assessed several DL algorithms focusing only on training and testing the models on the planning MRI only. …”
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Deep Q-Networks for Minimizing Total Tardiness on a Single Machine by Kuan Wei Huang, Bertrand M. T. Lin

“…Due to its computational intractability, exact approaches such as dynamic programming algorithms and branch-and-bound algorithms struggle to produce optimal solutions for large-scale instances in a reasonable time. …”
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Research of Physical and Mechanical Properties of Self-Compacting Concrete Based on Polyfractional Binder by Meiram M. Begentayev, Daniyar A. Akhmetov, Rauan E. Lukpanov, Erzhan I. Kuldeyev, Zhanar O. Zhumadilova, Tolebi Myrzaliyev, Duman S. Dyussembinov, Aigerim K. Tolegenova

“…A software and calculation complex featuring a three-dimensional modeling algorithm, Drop and Roll, was used to select the optimal composition. …”
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Preliminary analysis of acoustic detection of the Red-throated Caracara in northern Costa Rica by Roberto Vargas-Masís, Diego Quesada

“…Advances in automatic acoustic detection have transformed bird ecology, allowing researchers to analyze bird populations using pattern matching algorithms, machine learning, and random forest models. …”
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Functional Monitoring of Patients With Knee Osteoarthritis Based on Multidimensional Wearable Plantar Pressure Features: Cross-Sectional Study by Junan Xie, Shilin Li, Zhen Song, Lin Shu, Qing Zeng, Guozhi Huang, Yihuan Lin

“…Furthermore, model stacking and average ensemble learning methods were adopted to further improve the generalization performance of the model. …”
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Analysis and Recommendation of Outdoor Activities for Smart City Users Based on Real-Time Contextual Data by S. R. Mani Sekhar, D. M. Mushtaq Ahmed, G. M. Siddesh

“…It contributes to the growing field of Smart Cities by introducing a scalable and adaptable framework that harnesses the power of deep learning to improve urban living. The result shows that the proposed air pollution model predicted 96.06700 PM2.5 concentration levels, subsequently the temperature model predicted 14.06800∘C. …”
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Robust EEG Characteristics for Predicting Neurological Recovery from Coma After Cardiac Arrest by Meitong Zhu, Meng Xu, Meng Gao, Rui Yu, Guangyu Bin

“…By integrating machine learning (ML) algorithms, such as Gradient Boosting Models and Support Vector Machines, with SHAP-based feature visualization, robust screening methods were applied to ensure the reliability of predictions. …”
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AI-powered approaches for enhancing remote sensing-based water contamination detection in ecological systems by Li Yang, Zhang Ziwen, Xinhao Lin, Junmiao Hei, Yixiao Wang, Ang Zhang

“…Recent advancements in artificial intelligence (AI) offer promising solutions to enhance water contamination detection, particularly by leveraging machine learning algorithms and sensor networks for continuous monitoring.MethodsThis paper presents a novel AI-powered approach for improving water contamination detection, which incorporates real-time data processing and predictive modeling to identify contamination events and optimize response strategies. …”
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Practical Recommendations for Artificial Intelligence and Machine Learning in Antimicrobial Stewardship for Africa by Tafadzwa Dzinamarira, Elliot Mbunge, Claire Steiner, Enos Moyo, Adewale Akinjeji, Kaunda Yamba, Loveday Mwila, Claude Mambo Muvunyi

“…The deployment of AI‐driven solutions presents unprecedented opportunities for optimizing treatment regimens, predicting resistance patterns, and improving clinical workflows. …”
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A Crowd Counting and Localization Network Based on Adaptive Feature Fusion and Multi-Scale Global Attention Up Sampling by Min Wang, Li Huang, Jingke Yan, Jin Huang, Tao Yang

“…The F1-m scores obtained on the SHHA and SHHB datasets reach 72.9% and 79.4% respectively, significantly improving the model’s performance.Finally, this paper extends the application of crowd counting and localization algorithms to different domains such as citrus orchards, vehicles, and campus crowds. …”
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Enhancing Autonomous Driving Perception: A Practical Approach to Event-Based Object Detection in CARLA and ROS by Jingxiang Feng, Peiran Zhao, Haoran Zheng, Jessada Konpang, Adisorn Sirikham, Phuri Kalnaowakul

“…While the previous research on event-based object detection has predominantly focused on algorithmic enhancements via advanced preprocessing and network optimizations to improve detection accuracy, the practical engineering and integration challenges of deploying these sensors in real-world systems remain underexplored. …”
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VP-SFDA: Visual Prompt Source-Free Domain Adaptation for Cross-Modal Medical Image by Yixin Chen, Yan Wang, Zhaoheng Xie

“…The second stage is the adaptation process, which aims at optimizing the segmentation model from the source domain to the target domain. …”
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Research on machine vision online monitoring system for egg production and quality in cage environment by Zhenlong Wu, Hengyuan Zhang, Cheng Fang

“…The core of the system, an enhanced You Only Look Once Version 8-small (YOLOv8s) model, was augmented by substituting the Residual Network-18 backbone and integrating the Shuffle Attention mechanism, significantly improving egg detection precision. …”
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Image-Based Detection and Classification of Malaria Parasites and Leukocytes with Quality Assessment of Romanowsky-Stained Blood Smears by Jhonathan Sora-Cardenas, Wendy M. Fong-Amaris, Cesar A. Salazar-Centeno, Alejandro Castañeda, Oscar D. Martínez-Bernal, Daniel R. Suárez, Carol Martínez

“…Leukocyte detection employed optimal thresholding segmentation utility (OTSU) thresholding, binary masking, and erosion, followed by the connected components algorithm. …”
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Using Geospatial Intelligence to Enhance Voting Access in Local Elections for People with Disabilities by A. Cohen, S. Dalyot

“…This study leverages geospatial intelligence to enhance voting accessibility by developing an algorithmic approach that helps individuals locate the nearest Accessible Polling Station (APS). …”
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