Recoating performance of fresh and weathered wood surfaces through atmospheric dielectric barrier discharge plasma activation

Wood Material Science and Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 16

Published: March 3, 2025

Language: Английский

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Leveraging swin transformer with ensemble of deep learning model for cervical cancer screening using colposcopy images

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 6, 2025

Cervical cancer (CC) is the leading cancer, which mainly affects women worldwide. It generally occurs from abnormal cell evolution in cervix and a vital functional structure uterus. The importance of timely recognition cannot be overstated, has led to various screening methods such as colposcopy, Human Papillomavirus (HPV) testing, Pap smears identify potential threats enable early intervention. Early detection during precancerous phase crucial, it provides an opportunity for effective treatment. diagnosis CC depend on colposcopy cytology models. Deep learning (DL) appropriate technique computer vision, developed latent solution increase efficiency accuracy when equated conventional clinical inspection models that are vulnerable human error. This study presents Leveraging Swin Transformer with Ensemble Learning Model Cancer Screening (LSTEDL-CCS) images. presented LSTEDL-CCS aims detect classify Initially, wiener filtering (WF) model used image pre-processing. Next, swin transformer (ST) network utilized feature extraction. For process, ensemble method performed by employing three models, namely autoencoder (AE), bidirectional gated recurrent unit (BiGRU), deep belief (DBN). Finally, hyperparameter tuning DL techniques using Pelican Optimization Algorithm (POA). A comprehensive experimental analysis conducted, results evaluated under diverse metrics. performance validation methodology portrayed superior value 99.44% over existing

Language: Английский

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Heat transfer and temperature distribution of manufacturing laminated veneer lumber using high-frequency heating: Finite element simulation and experimental validation

Construction and Building Materials, Journal Year: 2025, Volume and Issue: 479, P. 141437 - 141437

Published: April 25, 2025

Language: Английский

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Prediction of Biochar Adsorption of Uranium in Wastewater and Inversion of Key Influencing Parameters Based on Ensemble Learning

Toxics, Journal Year: 2024, Volume and Issue: 12(10), P. 698 - 698

Published: Sept. 26, 2024

With the rapid development of industrialization, problem heavy metal wastewater treatment has become increasingly serious, posing a serious threat to environment and human health. Biochar shows great potential for application in field treatment; however, biochars prepared from different biomass sources experimental conditions have physicochemical properties, resulting differences their adsorption capacity uranium, which limits wide treatment. Therefore, there is an urgent need deeply explore optimize key parameter settings biochar significantly improve its capacity. This paper combines nonlinear mapping capability SCN ensemble learning advantage Adaboost algorithm based on existing data The accuracy model evaluated by metrics such as coefficient determination (R

Language: Английский

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A Two-Tiered Bidirectional Atrous Spatial Pyramid Pooling-Based Semantic Segmentation Model for Landslide Classification using Remote Sensing Images

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 181316 - 181331

Published: Jan. 1, 2024

Language: Английский

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