deep learning – Page 2

Detection and classification of Shiitake mushroom fruiting bodies based on Mamba YOLO

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Researchers developed an artificial intelligence system called Mamba-YOLO that can automatically detect and grade shiitake mushrooms for harvest. The system looks at images of mushrooms and identifies which ones are ready to pick based on their size, maturity, and surface texture characteristics. With 98.89% accuracy and fast processing speed of 8.3 milliseconds, this technology could help automate mushroom harvesting and reduce labor costs for farmers. The compact model design also allows it to be installed on robotic harvesting machines.

Hybrid Deep Learning Framework for High-Accuracy Classification of Morphologically Similar Puffball Species Using CNN and Transformer Architectures

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Scientists developed an artificial intelligence system that can automatically identify eight different types of puffball mushrooms from photographs with 95% accuracy. The study compared five different AI models and found that a modern convolutional neural network called ConvNeXt-Base was the best at telling apart puffball species that look very similar to each other. This technology could help amateur mushroom enthusiasts, researchers, and nature conservationists accurately identify these fungi without needing a microscope or laboratory tests.

Research Keyword: deep learning

Detection and classification of Shiitake mushroom fruiting bodies based on Mamba YOLO

Hybrid Deep Learning Framework for High-Accuracy Classification of Morphologically Similar Puffball Species Using CNN and Transformer Architectures