Image-Based Classification of Olive Varieties Native to Turkiye Using Multiple Deep Learning Architectures: Analysis of Performance, Complexity, and Generalization

The study evaluates ten deep learning architectures for classifying five olive varieties in Turkey using image-based datasets, finding EfficientNetV2-S to have the highest accuracy and EfficientNetB0 to offer the best balance between accuracy and computational efficiency. This highlights the importance of parametric efficiency over model depth when data is limited, providing valuable insights for content creators working with constrained datasets.

Read the full article at arXiv cs.CV (Vision)

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