A Cloud-Based Intelligence System for Asian Rust Risk Analysis in Soybean Crops by Ricardo Alexandre Neves, Paulo Estevão Cruvinel

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Towards decoding motor imagery from EEG signal using optimized back propagation neural network with honey badger algorithm by Zainab Hadi-Saleh, Mohammad Mosleh, Mohamed Adel Al-Shahe, Mahdi Mosleh

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Research on Time Series Interpolation and Reconstruction of Multi-Source Remote Sensing AOD Product Data Using Machine Learning Methods by Huifang Wang, Min Wang, Pan Jiang, Fanshu Ma, Yanhu Gao, Xinchen Gu, Qingzu Luan

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Improvement and Optimization of Feature Selection Algorithm in Swarm Intelligence Algorithm Based on Complexity by Bingsheng Chen, Huijie Chen, Mengshan Li

“…Feature selection, as an effective data processing method, has become a hot research topic in the fields of machine learning, pattern recognition, and data mining and has received extensive attention and attention. …”
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Revealing the heterogeneity of treatment resistance in less‐defined subtype diffuse large B cell lymphoma patients by integrating programmed cell death patterns and liquid biopsy by Wei Hua, Jie Liu, Yue Li, Hua Yin, Hao‐Rui Shen, Jia‐Zhu Wu, Yi‐Lin Kong, Bi‐Hui Pan, Jun‐Heng Liang, Li Wang, Jian‐Yong Li, Rui Gao, Jin‐Hua Liang, Wei Xu

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Extreme gradient and boosting algorithm for improved bias-correction and downscaling of CMIP6 GCM data across indian river basin by Chandni Thakur, Venkatesh Budamala, KS Kasiviswanathan, Claudia Teutschbein, Bankaru-Swamy Soundharajan

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An evaluation of single and multi-date Landsat image classifications using random forest algorithm in a semi-arid savanna of Ghana, West Africa by Eric Adjei Lawer

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The spatiotemporal distribution patterns and impact factors of bird species richness: A case study of urban built-up areas in Beijing, China by Zheran Zhai, Siyao Liu, Zimeng Li, Ruijie Ma, Xiaoyu Ge, Haidong Feng, Yang Shi, Chen Gu

“…Additionally, this study employed three tree-based machine learning algorithms—Decision Tree (DT), Random Forest (RF), and Extreme Gradient Boosting (XGBoost)—to investigate the influence of environmental factors on bird species distribution within urban built-up areas. …”
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Diverse regulated cell death patterns and immune traits in kidney allograft with fibrosis: a prediction of renal allograft failure based on machine learning, single-nucleus RNA seq... by Yuqing Li, Jiandong Zhang, Xuemeng Qiu, Yifei Zhang, Jiyue Wu, Qing Bi, Zejia Sun, Wei Wang

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Lightweight Anomaly-Based Detection Using Cuckoo Search Algorithm and Decision Tree to Mitigate Man-in-the-Middle Attacks in DNS by Ramahlapane Lerato Moila, Mthulisi Velempini

“…The proposed model utilizes machine learning algorithms and statistical analysis techniques to ensure that the analysis of DNS query patterns can efficiently detect anomalies associated with the MitM. …”
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Comparison of mask R-CNN and YOLOv8-seg for improved monitoring of the PCB surface during laser cleaning by Lu Qiao, Markus Veltrup, Bernd Mayer

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A Comprehensive Review of EEG-Based Seizure Detection Techniques by Goldwyn Sudhakar Jebaraj, Konguvel Elango

“…Despite considerable progress in EEG signal acquisition, preprocessing methodologies, and the application of machine learning algorithms, significant challenges persist due to the inherent complexity and inter-subject variability observed in seizure patterns. …”
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ADAPTIVE VISION AI by V. Vodyanitskyi, V. Yuskovych-Zhukovska

“…Computer vision technologies rely on pattern recognition, machine learning, and neural networks to allow computers to break down images, interpret data, and identify features. …”
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Enhanced Kidney Stone Detection and Classification Using SVM and LBP Features by Hawkar K. Hama, Hamsa D. Majeed, Goran Saman Nariman

“…The segmentation phase follows, accurately identifying the kidney’s edges and regions of interest for effective feature extraction. The Local Binary Pattern (LBP) technique, combined with the support vector machine (SVM) algorithm serves as the primary components of the proposed model. …”
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Advanced Leaf Classification Using Multi-Layer Perceptron for Smart Crop Management by Sara Mumtaz, Mohammed Alshehri, Yahya AlQahtani, Abdulmonem Alshahrani, Bayan Alabdullah, Haifa F. Alhasson, Hui Liu

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Assessing training needs and influencing factors among personnel at centers for disease control and prevention in northeast China: a cross-sectional study framed by SDT and TPB usi... by Kexin Wang, Peng Wang, Min Wei, Yanping Wang, Huan Liu, Ruiqian Zhuge, Qunkai Wang, Nan Meng, Yiran Gao, Yuxuan Wang, Lijun Gao, Jingjing Liu, Xin Zhang, Mingli Jiao, Qunhong Wu

“…SHapley Additive exPlanations (SHAP) were used to explain the output of the optimal machine learning model. Results This study identified the four subgroups of competency patterns, including novice (25.3%), public health experts (15.1%), potential expansion talents (24.7%), and versatile talents (34.9%). …”
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Energy Efficiency in Measurement and Image Reconstruction Processes in Electrical Impedance Tomography by Barbara Stefaniak, Tomasz Rymarczyk, Dariusz Wójcik, Marta Cholewa-Wiktor, Tomasz Cieplak, Zbigniew Orzeł, Janusz Gudowski, Ewa Golec, Michał Oleszek, Marcin Kowalski

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Classification of Paddy Rice Planting Area Through Feature Selection Method Using Sentinel-1/2 Time Series Images by Shiyu Zhang, Pengao Li, Yong Xie, Wen Shao, Xueru Tian

“…The optimal feature subset was selected through the feature selection method, and machine learning algorithms were optimized for paddy rice planting area classification. …”
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Identification of Alzheimer’s disease biomarkers and their immune function characterization by Mingkai Lin, Yue Zhou, Peixian Liang, Ruoyi Zheng, Minwei Du, Xintong Ke, Wenjing Zhang, Pei Shang

“…Results Five biomarkers (RBM3, GOLGA8A, ALS2, FSD2, and LOC100287628) were identified using machine learning algorithms. Single-cell analysis revealed distinct expression patterns of these biomarkers in astrocytes from AD samples compared to normal samples. …”
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Study on the Method of Vineyard Information Extraction Based on Spectral and Texture Features of GF-6 Satellite Imagery by Xuemei Han, Huichun Ye, Yue Zhang, Chaojia Nie, Fu Wen

“…However, the spectral reflectance similarities between grapevines and other orchard vegetation lead to persistent misclassification and omission errors across various machine learning algorithms. As a perennial vine plant, grapes are cultivated using trellis systems, displaying regular row spacing and distinctive strip-like texture patterns in high-resolution satellite imagery. …”
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