An involution-infused DenseNet student, compressed via knowledge distillation and weight pruning, achieves 96.99 to 98.63 percent accuracy with about 0.29 million parameters on two plant disease datasets.
Areviewofplantleaffungaldiseasesanditsenvironmentspeciation.Bioengineered,10(1):409– 424, 2019
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Involution-Infused DenseNet with Two-Step Compression for Resource-Efficient Plant Disease Classification
An involution-infused DenseNet student, compressed via knowledge distillation and weight pruning, achieves 96.99 to 98.63 percent accuracy with about 0.29 million parameters on two plant disease datasets.