Target image detection algorithm of complex road scene based on improved multi-scale adaptive feature fusion technology by Xu Zhaosheng, Liao Zhongming, Xiao Xiaoyong, Ahmad Suzana, Mat Diah Norizan, Ismail Azlan

“…The simulation outcomes illustrate that the recommended IMSAFFT model increases the accuracy ratio of 98.4%, target image detection ratio of 97.4%, traffic prediction rate of 96.5%, processing speed rate of 10.4% and F1-score ratio of 95.4% compared to other existing models.…”
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Air Traffic Trends and UAV Safety: Leveraging Automatic Dependent Surveillance–Broadcast Data for Predictive Risk Mitigation by Prasad Pothana, Paul Snyder, Sreejith Vidhyadharan, Michael Ullrich, Jack Thornby

“…To enhance the safe and efficient integration of UAVs into airport environments, this paper presents an analysis of temporal statistical patterns in flight traffic, the predictive modeling of future traffic trends using machine learning, and the identification of optimal time windows for UAV operations within airports. …”
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Optimization of Cocoa Pods Maturity Classification Using Stacking and Voting with Ensemble Learning Methods in RGB and LAB Spaces by Kacoutchy Jean Ayikpa, Abou Bakary Ballo, Diarra Mamadou, Pierre Gouton

“…Determining the maturity of cocoa pods early is not just about guaranteeing harvest quality and optimizing yield. It is also about efficient resource management. Rapid identification of the stage of maturity helps avoid losses linked to a premature or late harvest, improving productivity. …”
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Prediction of Pt, Ir, Ru, and Rh complexes light absorption in the therapeutic window for phototherapy using machine learning by V. Vigna, T. F. G. G. Cova, A. A. C. C. Pais, E. Sicilia

“…The model is efficient, fast, and resource-light, using decision tree-based algorithms that provide interpretable results. …”
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Development of a 101.6K liquid‐phased probe for GWAS and genomic selection in pine wilt disease‐resistance breeding in Masson pine by Jingyi Zhu, Qinghua Liu, Shu Diao, Zhichun Zhou, Yangdong Wang, Xianyin Ding, Mingyue Cao, Dinghui Luo

“…The DNNGP (deep neural network‐based method for genomic prediction) model demonstrated superior performance in GS, achieving a maximum predictive accuracy of 0.71. …”
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A Novel Dynamic Context Branch Attention Network for Detecting Small Objects in Remote Sensing Images by Huazhong Jin, Yizhuo Song, Ting Bai, Kaimin Sun, Yepei Chen

“…Within each branch, a Context Adaptive Selection Module (CASM) dynamically weights information, allowing the model to focus on the most relevant context. To further enhance performance, we introduce an Efficient Branch Attention (EBA) module that adaptively reweights the parallel branches, prioritizing the most discriminative ones. …”
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NDL-Net: A Hybrid Deep Learning Framework for Diagnosing Neonatal Respiratory Distress Syndrome From Chest X-Rays by Malik Muhammad Arslan, Xiaodong Yang, Nan Zhao, Lei Guan, Tao Cui, Daniyal Haider

“…<italic>Results:</italic> The architecture combines MobileNetV3 Large for efficient image processing and ResNet50 for detecting complex patterns essential for NRDS identification. …”
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Integration of Metro Tunnel Equipment Safety Early Warning System Based on Static-Dynamic Analysis by FAN Lele, YU Ze, HE Likun, YUAN Shijie, LAN Jie, YU Weizhi, LIU Jian

“…It achieves timely identification of abnormal equipment vibration and risk forecasting, forming a unified and efficient operation and maintenance management mechanism, and effectively reduces the risk of equipment failure.…”
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City-scale industrial tank detection using multi-source spatial data fusion by Zhibao Wang, Mingyuan Zhu, Lu Bai, Jinhua Tao, Mei Wang, Xiaoqing He, Anna Jurek-Loughrey, Liangfu Chen

“…The integration from multiple data sources provides an accurate and efficient solution for the identification of industrial storage tanks within urban areas.…”
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Developing a new cleavable crosslinker reagent for in-cell crosslinking by Fränze Müller, Bogdan R. Brutiu, Iakovos Saridakis, Thomas Leischner, Micha J. Birklbauer, Manuel Matzinger, Mathias Madalinski, Thomas Lendl, Saad Shaaban, Viktoria Dorfer, Nuno Maulide, Karl Mechtler

“…We tested DiSPASO employing three different copper-based enrichment strategies using model systems with increasing complexity (Cas9-Halo, purified ribosomes, live cells). …”
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Rapid Flood Inundation Mapping for Effective Management: A Machine Learning and Pixel‐Based Classification Approach in Feni District, Bangladesh by Kabir Uddin, Sazzad Hossain, Birendra Bajracharya, Bayes Ahmed, Md. Khairul Islam

“…Effective flood management requires precise and timely flood mapping methodologies to adopt disaster risk reduction strategies and enable efficient response efforts. This study presents an approach that facilitates timely flood identification, improving emergency response, evacuation initiatives, relief distribution, and disaster risk reduction. …”
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MDFT-GAN: A Multi-Domain Feature Transformer GAN for Bearing Fault Diagnosis Under Limited and Imbalanced Data Conditions by Chenxi Guo, Vyacheslav V. Potekhin, Peng Li, Elena A. Kovalchuk, Jing Lian

“…To improve classification performance, an Enhanced Hybrid Visual Transformer (EH-ViT) is constructed by coupling a lightweight convolutional stem with a ViT encoder, enabling robust and discriminative fault identification. Beyond performance metrics, this work also incorporates a Grad-CAM-based interpretability scheme to visualize hierarchical feature activation patterns within the discriminator, providing transparent insight into the model’s decision-making rationale across different fault types. …”
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In Vitro Differentiation and Maturation of Human Embryonic Stem Cell into Multipotent Cells by Amer Mahmood, Claudio Napoli, Abdullah Aldahmash

“…Basic science in the field of embryonic development, stem cell differentiation, and tissue engineering has offered important insights into key pathways and scaffolds that regulate hESC differentiation, which have produced advances in modeling gastrulation in culture and in the efficient induction of endoderm, mesoderm, ectoderm, and many of their downstream derivatives. …”
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Strategies and Challenges for Unmanned Aerial Vehicle-Based Continuous Inspection and Predictive Maintenance of Solar Modules by Ghulam E. Mustafa Abro, Amjad Ali, Sufyan Ali Memon, Tayab Din Memon, Faheem Khan

“…This study emphasizes the significance of early defect identification on solar farm efficiency and delineates a strategy for improving the reliability and cost-effectiveness of photovoltaic module inspections via UAV technology.…”
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APEX: an automated cloud-native material property explorer by Zhuoyuan Li, Tongqi Wen, Yuzhi Zhang, Xinzijian Liu, Chengqian Zhang, A. S. L. Subrahmanyam Pattamatta, Xiaoguo Gong, Beilin Ye, Han Wang, Linfeng Zhang, David J. Srolovitz

“…Abstract The ability to rapidly evaluate materials properties through atomistic simulation approaches is the foundation of many new artificial intelligence-based approaches to materials identification and design. This depends on the availability of accurate descriptions of atomic bonding and an efficient means for determining materials properties. …”
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Deep learning for human locomotion analysis in lower-limb exoskeletons: a comparative study by Omar Coser, Omar Coser, Christian Tamantini, Christian Tamantini, Matteo Tortora, Matteo Tortora, Leonardo Furia, Rosa Sicilia, Loredana Zollo, Paolo Soda, Paolo Soda

“…Model explainability is assessed via SHAP analysis to guide sensor selection.ResultsIMU-only configurations matched or outperformed those using both IMU and EMG, supporting a more efficient setup. …”
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Preference for HIV testing among community residents in Yunnan Province, China: results from a discrete choice experiment by Jingwen Yang, Chenquan Qiu, Renhai Tang, Wenbin Dong, Enlong Yao, Huyunzhao Wang, Shuwen Lin, Minyang Xiao, Zuyang Zhang, Jin Niu, Liru Fu, Lijun Song, Xuehua Li, Yuhua Shi, Xiaowen Wang

“…Worrying that others know the test results is a significant factor influencing testing decision-making and the uptake of testing services. Adjusting the model of community-based HIV testing services according to the preferences of the target population could make it more efficient and effective for the general public, allowing for early detection of HIV infection.…”
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Using explainable machine learning and eye-tracking for diagnosing autism spectrum and developmental language disorders in social attention tasks by Adoración Antolí, Adoración Antolí, Francisco Javier Rodriguez-Lozano, José Juan Cañas, Julia Vacas, Julia Vacas, Fátima Cuadrado, Fátima Cuadrado, Araceli Sánchez-Raya, Araceli Sánchez-Raya, Carolina Pérez-Dueñas, Carolina Pérez-Dueñas, Juan Carlos Gámez-Granados

“…The resulting model enabled the identification of potential disorder-specific markers, such as the mean duration of visits to objects.ConclusionThese findings highlight the potential of applying XML techniques to eye-tracking data collected through tasks designed to capture features characteristic of neurodevelopmental conditions. …”
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Automated mold defects classification in paintings: A comparison of machine learning and rule-based techniques. by Hilman Nordin, Bushroa Abdul Razak, Norrima Mokhtar, Mohd Fadzil Jamaludin, Adeel Mehmood

“…This innovative method has the potential to transform the approach to managing mold defects in fine art paintings by offering a more precise and efficient means of identification. By enabling early detection of mold defects, this method can play a crucial role in safeguarding these invaluable artworks for future generations.…”
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Enhancing Tomato Leaf Disease Detection via Optimized VGG16 and Transfer Learning Techniques by Sandy Putra Siregar, Imam Akbari, Poningsih Poningsih, Anjar Wanto, Solikhun Solikhun

“…This paper offers an improved CNN through hyperparameter tuning and compares it to Transfer Learning models such as InceptionV3, NASNetMobile, and VGG16, which were chosen for their efficiency and accuracy. …”
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