Advances in the Automated Identification of Individual Tree Species: A Systematic Review of Drone- and AI-Based Methods in Forest Environments by Ricardo Abreu-Dias, Juan M. Santos-Gago, Fernando Martín-Rodríguez, Luis M. Álvarez-Sabucedo

“…Additionally, we discuss the challenges of model generalization across different forest ecosystems and propose future research directions, including the development of standardized datasets and improved model architectures for robust tree species classification. …”
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Transfer Learning based Image Classification of Diseased Tomato Leaves with Optimal Fine-Tuning combined with Heat Map Visualization by Sivakumar Palanıswamy, Vijayakumar Vaıthyam Rengarajan, Sandhya Devi Ramıah Subburaj

“…Computer Vision systems and advancements in deep learning-based modeling methodologies gained significant attention in smart farming. …”
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Hankel Tensor Subspace Representation for Remotely Sensed Image Fusion by Fei Ma, Qiang Qu, Feixia Yang, Guangxian Xu

“…To tackle these challenges, this article reformulates a novel image fusion model by incorporating Hankel tensor subspace representation (HTSR) for quality improvement of reconstruction images. …”
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Advancing Arabic Word Embeddings: A Multi-Corpora Approach with Optimized Hyperparameters and Custom Evaluation by Azzah Allahim, Asma Cherif

“…For instance, in the analogy test, a larger vocabulary size significantly improved outcomes, with the FastText skip-gram models excelling in accurately solving analogy questions. …”
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Neighborhood Information Aggregation and Multi-View Feature Extraction-Based Contrastive Graph Clustering by Liulong Yao, Jinrong Cui, Yazi Xie, Chengli Sun

“…Extensive experiments on five benchmark datasets show that our proposed method outperforms most other clustering algorithms.…”
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A Survey on Video Compression Optimization Techniques for Accuracy Enhancement in Video Analytics Applications (VAPs) by Kholidiyah Masykuroh, Hendrawan, Eueung Mulyana, Farhan Krishna

“…We examine traditional compression algorithms, machine learning-based approaches, dynamic parameter adjustment strategies, and hybrid models, each offering unique strengths and limitations. …”
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Artificial Intelligence and Smart Technologies in Safety Management: A Comprehensive Analysis Across Multiple Industries by Jiyoung Park, Dongheon Kang

“…AI-driven solutions, such as predictive analytics, machine learning algorithms, IoT sensor integration, and digital twin models, are shown to proactively identify and mitigate potential hazards, optimize energy consumption, and enhance operational efficiency. …”
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Precise application of water and fertilizer to crops: challenges and opportunities by Yingying Xing, Xiukang Wang

“…It examines the integration of advanced sensors, remote sensing, and machine learning algorithms in precision agriculture, assessing their roles in optimizing irrigation and nutrient management. …”
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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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Recent technical advancements and clinical applications of MR-guided radiotherapy in lung cancer treatment by Chi Ma, Xiao Wang, Ke Nie, Zhenyu Xiong, Keying Xu, Ning Yue, Yin Zhang

“…Additionally, MRgRT could potentially allow multileaf collimator (MLC) tracking to further improve the treatment efficiency. Recent technological innovations, including AI-powered auto-contouring algorithms, deep-learning (DL) based prediction models, and adaptive treatment strategies, further optimize MRgRT by improving workflow efficiency and reducing treatment time. …”
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Leveraging machine learning to proactively identify phishing campaigns before they strike by Kun Zhang, Haifeng Wang, Meiyi Chen, Xianglin Chen, Long Liu, Qiang Geng, Yu Zhou

“…These algorithms were chosen for their strong global search capabilities and adaptability to complex datasets, ensuring optimal parameter selection for improved model performance. …”
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A comprehensive review of artificial intelligence approaches for smart grid integration and optimization by Malik Ali Judge, Vincenzo Franzitta, Domenico Curto, Andrea Guercio, Giansalvo Cirrincione, Hasan Ali Khattak

“…The advanced metaheuristic algorithms are a good addition to the literature, they are still in emerging stages and their performance can further be improved. …”
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Artificial intelligence demonstrates potential to enhance orthopaedic imaging across multiple modalities: A systematic review by Umile Giuseppe Longo, Alberto Lalli, Guido Nicodemi, Matteo Giuseppe Pisani, Alessandro De Sire, Pieter D'Hooghe, Ara Nazarian, Jacob F. Oeding, Balint Zsidai, Kristian Samuelsson

“…Included were studies published between September 2018 and February 2024, which evaluated machine learning (ML) model effectiveness in improving orthopaedic imaging. …”
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Transfer Learning to Detect COVID-19 Automatically from X-Ray Images Using Convolutional Neural Networks by Mundher Mohammed Taresh, Ningbo Zhu, Talal Ahmed Ali Ali, Asaad Shakir Hameed, Modhi Lafta Mutar

“…The outstanding performance of these pretrained models can significantly improve the speed and accuracy of COVID-19 diagnosis. …”
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Integrating Tiny Machine Learning and Edge Computing for Real-Time Object Recognition in Industrial Robotic Arms by Nian-Ze Hu, Bo-An Lin, Yen-Yu Wu, Hao-Lun Huang, You-Xin Lin, Chih-Chen Lin, Po-Han Lu

“…By integrating visual recognition technology and multi-object recognition into robotic arms, the flexibility and automation of the production process were improved in this study. By applying tiny machine learning (TinyML) and machine vision algorithms, we integrated edge computing devices to control the robotic arms and identified objects precisely on the production line, with ultra-low energy consumption. …”
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Defining analytical skills for human resources analytics: A call for standardization by Konrad Kulikowski

“…PURPOSE: Human resources (HR) analytics systems, powered by big data, AI algorithms, and information technology, are increasingly adopted by organizations to enhance HR’s impact on business performance. …”
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Artificial intelligence in atrial fibrillation: emerging applications, research directions and ethical considerations by Ibrahim Antoun, Ibrahim Antoun, Ahmed Abdelrazik, Mahmoud Eldesouky, Xin Li, Georgia R. Layton, Georgia R. Layton, Georgia R. Layton, Mustafa Zakkar, Mustafa Zakkar, Mustafa Zakkar, Riyaz Somani, Riyaz Somani, G. André Ng, G. André Ng, G. André Ng

“…Furthermore, AI-powered remote monitoring integrates wearable-derived insights with real-time decision support, improving patient engagement and adherence. Despite these advances, significant challenges persist, including algorithm transparency, bias, data integration, and regulatory hurdles. …”
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多楔带轮增厚成形有限元模拟及试验 by 殷沙

“…The forming process of the multi-wedge belt pulley is proposed according to the structure.A 3D rigid-plastic FEA model of spinning thickening forming was established by the software,DEFORM.Based on the experimental data obtained through numerical simulation and orthogonal method,the influential of the processing parameters on the forming load including influential trend and the order of significance is determined in the process of thickening forming.Then,the optimization technology involving neural networks and genetic algorithms is utilized to optimize the processing parameters,and the optimum combination of processing parameters are acquired.Through CAE simulation and experimental verification,it is proved that the forming quality of thickening blank is improved and the forming load significantly decreases,thus protecting the spinning roller and spinning equipment.…”
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Validation of the vertical canopy cover profile products derived from GEDI over selected forest sites by Yu Li, Hongliang Fang, Yao Wang, Sijia Li, Tian Ma, Yunjia Wu, Hao Tang

“…The partial difference between GEDI CC and ALS CC is attributed to definitional discrepancies. Further improvement of the CC algorithm can be made by using vegetation-specific waveform processing algorithms and realistic ρv/ρg values.…”
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Transformer-Based Deep Learning for Mesoscale Eddy Detection in Sea Surface Temperature Maps by Chen Ji, Wenyang Xu, Xiangtian Zheng, Yasmeen Ahmed, Saad Ahmed Jamal, Fakhar Imam, Mohammed Saleh Ali Muthanna, Maha Ibrahim, Sajid Ullah, Dmitry E. Kucher

“…These eddies’ precise identification and categorization can improve climate modeling, ocean circulation research, and environmental surveillance. …”
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