Browsing by Author Nguyen, Ngoc Viet
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Plant-leaf diseases have become a significant threat to food security due to reducing the quantity and quality of agricultural products. Plant disease detection methods are commonly based on experience through manual observations of leaves. Developing fast, accurate, and automated techniques for identifying of crop diseases using computer vision and artificial intelligence (AI) can help overcome human shortcomings. In the current study, the EfficientNet architectures with pre-trained Noisy-Student weights were implemented using the transfer learning approach to classify leaf image-based healthy and diseased plant groups. The deep learning models were performed on the extended and enha... |
The assembly of primary nanoparticles to form hierarchical ultra-porous architectures is of great interest in various fields because of their extremely large surface area and porosity. In this work, the 3D ultra-porous γ-Fe2O3 nanocubes were synthesized by a simple method, which was derived from perfect Prussian Blue nanocubes by the oxidative decomposition process. The as-synthesized 3D γ-Fe2O3 nanocubes possess a large specific surface area and high porosity, which arise from the self-assembly of ultrafine nanoparticles. The 3D ultra-porous γ-Fe2O3 nanocubes-based sensors showed superior detection of acetone and ethanol with excellent sensitivity and rapid response time. The fantast... |
