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701
RRBM-YOLO: Research on Efficient and Lightweight Convolutional Neural Networks for Underground Coal Gangue Identification
Published 2024-10-01“…Coal gangue identification is the primary step in coal flow initial screening, which mainly faces problems such as low identification efficiency, complex algorithms, and high hardware requirements. …”
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702
Edge Artificial Intelligence (AI) for real-time automatic quantification of filariasis in mobile microscopy.
Published 2024-04-01“…It achieved an overall precision of 94.14%, recall of 91.90% and F1 score of 93.01% for the screening algorithm and 95.46%, 97.81% and 96.62% for the species differentiation algorithm respectively. …”
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703
A Three-Dimensional Phenotype Extraction Method Based on Point Cloud Segmentation for All-Period Cotton Multiple Organs
Published 2025-05-01“…Experimental data show that, in the task of organ segmentation throughout the entire cotton growth cycle, the ResDGCNN model achieved a segmentation accuracy of 67.55%, with a 4.86% improvement in mIoU compared to the baseline model. …”
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704
Sweetener identification using transfer learning and attention mechanism
Published 2024-12-01“…Accurate identification of the taste of compounds has helped in the screening and development of new sweeteners. This study proposes a deep learning model for sweetener identification based on transfer learning and attention mechanism. …”
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705
Road Perception for Autonomous Driving: Pothole Detection in Complex Environments Based on Improved YOLOv8
Published 2025-01-01“…To address this, this paper proposes an innovative improved algorithm, which is based on the YOLOv8 model, and introduces the MSF-HFEB module in the innovative design. …”
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706
Hydraulic Pump Fault Diagnosis Method Based on EWT Decomposition Denoising and Deep Learning on Cloud Platform
Published 2021-01-01“…Compared with ensemble empirical mode decomposition (EEMD) and complementary ensemble empirical mode decomposition (CEEMD), the results show that the axial piston pump fault diagnosis algorithm based on EWT and 1D-CNN has higher fault identification accuracy.…”
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707
Explainable machine learning for predicting lung metastasis of colorectal cancer
Published 2025-04-01“…We selected the best algorithm and visualized it using SHAP. We conducted a validation of the model utilizing data from a Chinese hospital to assess its practicality. …”
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708
Fecal occult blood affects intestinal microbial community structure in colorectal cancer
Published 2025-01-01“…Characteristic gut bacteria were screened, and various machine learning algorithms were applied to construct CRC risk prediction models. …”
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709
A Fuzzy Supplier Selection Application Using Large Survey Datasets of Delivery Performance
Published 2015-01-01“…A model is developed using fuzzy probability to screen survey data across relevant criteria for selecting suppliers based on fuzzy expected values. …”
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710
A Ship Underwater Radiated Noise Prediction Method Based on Semi-Supervised Ensemble Learning
Published 2025-07-01“…Second, a semi-supervised ensemble (ESS) framework integrating dynamic pseudo-label screening and uncertainty bias correction (UBC) is established, which can dynamically select pseudo-labels based on local prediction performance improvement and reduce the influence of pseudo-labels’ uncertainty on the model. …”
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711
Research on Feature Extraction of Performance Degradation for Flexible Material R2R Processing Roller Based on PCA
Published 2020-01-01“…The Jacobi iteration method was introduced to derive the algorithm for solving eigenvalue and eigenvector of the covariance matrix. …”
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712
Prognostic prediction of gastric cancer based on H&E findings and machine learning pathomics
Published 2024-12-01“…Features selected via minimum Redundancy - Maximum Relevance (mRMR)- recursive feature elimination (RFE) screening were used to train a model using the Gradient Boosting Machine (GBM) algorithm. …”
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713
Perceived age estimation from facial image and demographic data in young and middle-aged South Korean adults
Published 2024-12-01“…The averaging models of Lasso, XGBoost, and CatBoost showed a mean absolute error of 2.2944, indicating that this algorithm can be used as a screening method for general health status in the population.…”
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714
Conformal prediction quantifies wearable cuffless blood pressure with certainty
Published 2025-07-01“…First, a quantile loss-based Gradient Boosting Regression Tree (GBRT) model was trained to obtain ambulatory BP estimates along with model uncertainty. …”
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715
A clinical scoring system to prioritise investigation for tuberculosis among adults attending HIV clinics in South Africa.
Published 2017-01-01“…<h4>Participants</h4>Representative sample of adult HIV clinic attendees; data from participants reporting ≥1 symptom on the WHO screening tool were split 50:50 to derive, then internally validate, a prediction model.…”
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716
Permeability Predictions for Tight Sandstone Reservoir Using Explainable Machine Learning and Particle Swarm Optimization
Published 2022-01-01“…The particle swarm optimization algorithm is then used to optimize the hyperparameters of the XGBoost model. …”
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717
The Chaotic Prediction for Aero-Engine Performance Parameters Based on Nonlinear PLS Regression
Published 2012-01-01“…At the same time, the forecast error is less than that of nonlinear PLS algorithm through bootstrap test screening.…”
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718
Explainable illicit drug abuse prediction using hematological differences
Published 2025-08-01“…Abstract This study aimed to develop a reliable and explainable predictive model for illicit drug use (IDU). The model uses a machine learning (ML) algorithm to predict IDU using hematological differences between illicit drug users (IDUr) and non-users (n-IDUr). …”
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719
FedeAMR-CFF: A Federated Automatic Modulation Recognition Method Based on Characteristic Feature Fine-Tuning
Published 2025-06-01“…Specifically, the clients extract representative features through distance-based metric screening, and the server aggregates model parameters via the FedAvg algorithm and fine-tunes the model using the collected features. …”
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720
Mining hypertension predictors using decision tree: Baseline data of Kharameh cohort study
Published 2024-12-01“…This model can be useful for early screening and improving preventive and curative health services in health promotion. …”
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