Synergizing residual and dense architectures for fine-grained oil palm grading : a deep feature concatenation approach
Accurate grading of Oil Palm Fresh Fruit Bunches (FFB) is pivotal for maximizing agricultural yield, yet manual assessment in unstructured environments remains labor-intensive and subjective. While Convolutional Neural Networks (CNNs) offer an automated solution, the conventional strategy of scaling network depth often yields diminishing returns or overfitting on moderately sized datasets. To over
