Karib Shams on Muck Rack

Karib Shams

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Articles

Benchmarking hybrid CNN and transformer backbones with graph convolution networks (GCN) for flower growth-stage classification

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By Aritra Das, raihan islam, Ahmed Reza, Karib Shams, Shamim H. Ripon
| Nature Verified
Abstract Accurate recognition of flower growth stages is important for plant phenotyping but remains challenging due to subtle visual differences and limited labeled data. This study proposes a hybrid CNN/Transformer + GCN framework for fine-grained flower growth-stage classification. A new dataset, BD Flower Growth, is introduced with 3,889 original images from eight Bangladeshi flower species, categorized into three stages (early, mid, full), forming 24 classes.
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