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SerpensGate-YOLOv8: an enhanced YOLOv8 model for accurate plant disease detection
Published 2025-01-01Get full text
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584
On-Site Detection of Ca and Mg in Surface Water Using Portable Laser-Induced Breakdown Spectroscopy
Published 2025-01-01Get full text
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585
Study on Medicinal Forest Plants in Ifo, Ogun State, Nigeria, and Factors Shaping Usage Patterns
Published 2024-03-01Get full text
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586
Effect of 26 Years of Intensively Managed Carya cathayensis Stands on Soil Organic Carbon and Fertility
Published 2014-01-01Get full text
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587
Details on the transport of European eel larvae through the Strait of Gibraltar into the Mediterranean Sea
Published 2025-01-01Get full text
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588
Genome-wide identification and expression analysis of the WRKY gene family in Mikania micrantha
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589
Fabrication and Characterization of Regenerated Cellulose Films Using Different Ionic Liquids
Published 2014-01-01Get full text
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590
Evolution and Attribution Analysis of Habitat Quality in China’s First Batch of National Parks
Published 2024-12-01Get full text
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591
Assessing and Mapping Erosion Risk for Velikoy Sub-watershed within Coruh River Basin in Turkey
Published 2018-07-01Get full text
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592
Overview of Deep Learning and Nondestructive Detection Technology for Quality Assessment of Tomatoes
Published 2025-01-01Get full text
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593
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Cultivar Evaluation and Essential Test Locations Identification for Sugarcane Breeding in China
Published 2014-01-01Get full text
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597
Digital mapping of soil organic carbon in a plain area based on time-series features
Published 2025-02-01Get full text
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598
Overview of Recent Advances in Canine Parvovirus Research: Current Status and Future Perspectives
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Study on Intelligent Classing of Public Welfare Forestland in Kunyu City
Published 2025-01-01“…The main contributions of this work are as follows: A machine learning model was developed using integrated data from the Third National Land Survey of China, including forestry, grassland, and wetland datasets. Unlike previous approaches, the SVM model is optimized with Grid Search (GS), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) to automatically determine classification parameters, overcoming the limitations of manual rule-based methods. …”
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