HIGHLIGHTS
SUMMARY
Historically, the recognition task was relying on algorithms that needs handcrafted features, which were processed using relatively simple discriminative models such as linear classifiers or support vector machines (SVM) (Halevy et_al, 2009; Rumpf et_al, 2012; Wäldchen and Mäder, 2018; Madsen et_al, 2020). To achieve good accuracy, DL models need very large datasets for their requirements as data-hungry neural_networks (Halevy et_al, 2009; Madsen et_al, 2020). The dataset was collected from 19 public datasets (The TensorFlow Team, Flowers; Kumar et_al, 2012a; Nilsback and Zisserman; Cassava disease classification (Kaggle); Olsen et_al, 2019; Söderkvist . . .
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