HAFREE: A Heatmap-Based Anchor-Free Detector for Apple Defect Detection by Nguyen Bui Ngoc Han, Ju-Hwan Lee, Dang Thanh Vu, Iqbal Murtza, Hyoung-Gook Kim, Jin-Young Kim

“…We introduce a multiscale feature fusion block, targeting small objects by incorporating local and global contextual information. …”
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A Comparative Study of a Deep Reinforcement Learning Solution and Alternative Deep Learning Models for Wildfire Prediction by Cristian Vidal-Silva, Roberto Pizarro, Miguel Castillo-Soto, Ben Ingram, Claudia de la Fuente, Vannessa Duarte, Claudia Sangüesa, Alfredo Ibañez

“…Wildfires pose an escalating threat to ecosystems and human settlements, making accurate forecasting essential for early mitigation. This study compared three deep learning models for wildfire prediction: Deep Reinforcement Learning (DRL) with Actor–Critic architecture, Convolutional Neural Network (CNN), and Transformer-based models. …”
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PneumoNet: Artificial Intelligence Assistance for Pneumonia Detection on X-Rays by Carlos Antunes, João M. F. Rodrigues, António Cunha

“…Using multiple datasets mitigates biases from single-source data, addresses variations in patient demographics, and allows for meaningful performance comparisons with prior research. …”
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A Hybrid Security Framework for Train-to-Ground (T2G) Communication Using DOA-Optimized BPNN Detection, Bayesian Risk Scoring, and RL-Based Response by Chaoyuan Sun, Weijiao Zhang, Peng Sun, Hui Wang, Chunhui Yang

“…Finally, a Q-learning-based reinforcement learning (RL) module dynamically selects optimal defense actions based on identified risk levels and attack patterns to mitigate system threats. Experimental results demonstrate improved performance in both multi-class and binary classification tasks compared to conventional methods. …”
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A Collaborative Multi-Agent Reinforcement Learning Approach for Non-Stationary Environments with Unknown Change Points by Suyu Wang, Quan Yue, Zhenlei Xu, Peihong Qiao, Zhentao Lyu, Feng Gao

“…In non-stationary scenarios featuring abrupt environmental changes, experiments demonstrate that MACPH outperforms baseline algorithms such as DDPG, MADDPG, and MATD3 in terms of reward performance, adaptation speed, learning stability, and robustness. …”
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Tractor Path Tracking Control Method Based on Prescribed Performance and Sliding Mode Control by Liwei Zhu, Weiming Sun, Qian Zhang, En Lu, Jialin Xue, Guohui Sha

“…The results demonstrate that compared with the traditional SMC method, the proposed method effectively mitigates the impact of complex farmland conditions, reducing path tracking errors while enforcing strict error constraints. …”
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Transformative Catalytic Carbon Conversion Enabling Superior Graphitization and Nanopore Engineering in Hard Carbon Anodes for Sodium‐Ion Batteries by Guilai Zhang, Hong Gao, Dingyi Zhang, Jun Xiao, Limeng Sun, Jiayi Li, Congcong Li, Yiwen Sun, Xinyao Yuan, Peng Huang, Yi Xu, Xin Guo, Yufei Zhao, Yong Wang, Yao Xiao, Guoxiu Wang, Hao Liu

“…As the temperature increases, trace amounts of zinc remain as single atoms in the hard carbon, featuring a uniform coordination structure. This mitigates the risk of electrochemically irreversible sites and enhances sodium‐ion transport rates. …”
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Tunable lattice thermal transport properties in high-entropy alloys through manipulating chemical short-range order guided by machine learning by Shihua Ma, Shijun Zhao

“…However, chemical short-range order (CSRO), a prominent yet not fully resolved structural feature in high-entropy materials, may mitigate the disordered effects. …”
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Data-driven insights into groundwater quality: machine and deep learning approaches by Gift Mbuzi, Abdur Rashid Sangi, Baha Ihnaini, Anil Carie, Sruthi Sivarajan, Satish Anamalamudi

“…The findings indicate the potential of predictive models based on AI in groundwater monitoring in real-time to enable better mitigation of contamination. This study contributes to the offering of reliable AI-based systems of monitoring the groundwater in real-life cases and sustainable resource management planning.…”
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Insights into landslide susceptibility: a comparative evaluation of multi-criteria analysis and machine learning techniques by Zuleide Ferreira, Bruna Almeida, Ana Cristina Costa, Manoel do Couto Fernandes, Pedro Cabral

“…These findings underscore RF’s strength in LSM and highlight ML’s potential to support urban planning and mitigate risks in landslide-prone areas.…”
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Experimental and numerical investigations of cavity flame spread in double skin façade by Xukun Sun, Hideki Yoshioka, Takafumi Noguchi, Yuhei Nishio, Biao Zhou

“…Furthermore, the validated CFD modeling is applied to scenarios with extended cavity depths and varied opening shapes, indicating that a cavity depth of ≥0.7 m mitigates flame spread for an opening ratio of n ≥ 1. …”
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FuXi-DA: a generalized deep learning data assimilation framework for assimilating satellite observations by Xiaoze Xu, Xiuyu Sun, Wei Han, Xiaohui Zhong, Lei Chen, Zhiqiu Gao, Hao Li

“…By assimilating data from Advanced Geosynchronous Radiation Imager aboard Fengyun-4B, FuXi-DA consistently mitigates analysis errors and significantly improves forecast performance. …”
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Stimulation-Induced Artifact Removal of the Local Field Potential Through Hardware Design: Toward the Implantable Closed-Loop Deep Brain Stimulation by Yi-Hui Wu, Hsiao-Chun Lin, Chi-Wei Huang, Chung-Yu Wu, Ming-Dou Ker

“…This technology aims to identify abnormal biomarker signals within the brain, and create novel systems featuring sophisticated hardware configurations to generate improved therapeutic approaches and more favorable outcomes. …”
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Threat Vector–Hierarchical Attack Representation Model-Based Threat Modeling and Security Assessment for Satellite Networks by Junbeom Park, Taehoon Eom, Hyungeun Kim, Hyeonsu Park, Zizung Yoon, Jongsou Park

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Modified PHILOS system utilizing a single bone cement calcar screw achieves optimal fixation stability and promotes bone healing: a biomechanical study and corresponding case serie... by Chenyi Huang, Bing Liu, Zongchao Liu, Wenqiang Xu, Zhenming Hu

“…In response to this challenge, we presents a newly designed PHILOS plate featuring a single cannulated calcar screw. The biomechanical performance of this innovative device has been evaluated. …”
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Comparative analysis of machine learning models for predicting river water quality: a case study of the Zayandeh Rood River by Elham Fazel Najafabadi, Paria Shojaei, Mojgan Askarizadeh

“…Two dimensionality reduction techniques—PCA and correlation matrix-based feature reduction—were implemented to enhance model efficiency and mitigate multicollinearity. …”
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Optimized deep learning models for stress-based stroke prediction from EEG signals by Sivasankaran Pichandi, Gomathy Balasubramanian, Venkatesh Chakrapani, J. Samuel Manoharan

“…The proposed model is distinguished by its optimized hybrid optimization technique for feature extraction, aimed at stress and stroke prediction. …”
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Deep learning-based time series prediction for precision field crop protection by Tao He, Meijin Li, Dong Jin

“…By combining convolutional layers for spatial feature extraction, recurrent neural networks for temporal modeling, and attention mechanisms for data fusion, SADF-Net captures intricate spatial-temporal dependencies while ensuring robustness to noisy and incomplete data. …”
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The impact of nature relatedness on carbon labeling type selection and willingness to pay a carbon premium by Yu Yao, Xiaoxiao He, Zhenhua Liu

“…By enhancing access to environmental-friendly information, carbon labeling mitigates the asymmetry of carbon-related information between consumers and manufacturers. …”
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Deep learning-based improved transformer model on android malware detection and classification in internet of vehicles by Naif Almakayeel

“…The advanced behaviour of multi-data source fusion in autonomous driving models has mitigated recognition accuracy and effectualness for Android malware. …”
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