Cross-Architectural Mixture-of-Experts with Adaptive Soft Routing for Plant Leaf Disease Classification

arXiv:2606.23441 · cs.AI · Submitted 2026-06-22 · Read on arXiv

cs.AI

Submitted: 2026-06-22

Updated: 2026-06-22

Comments: 42 pages, 17 figures, 8 tables

Journal ref: Array, 2026

DOI: 10.1016/j.array.2026.101261

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 27× in this paper · explained in 1 episode
• Transformer — 22× in this paper · explained in 2 episodes
• Generalization — 20× in this paper · explained in 13 episodes
• Feature Extraction — 9× in this paper · explained in 2 episodes
• Adam — 7× in this paper · explained in 2 episodes
• Robustness — 7× in this paper · explained in 5 episodes
• Benchmark — 5× in this paper · explained in 2 episodes
• Mixture of Experts — 5× in this paper · explained in 2 episodes
• Regularization — 5× in this paper · explained in 3 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Alignment — 4× in this paper · explained in 1 episode
• Ablation study — 3× in this paper · explained in 1 episode
• Adaptability — 3× in this paper · explained in 1 episode
• Aggregation — 3× in this paper · explained in 1 episode
• Contextual Understanding — 3× in this paper · explained in 2 episodes
• Feature Engineering — 3× in this paper · explained in 3 episodes
• Feature Projection Module — 3× in this paper
• Feature Selection — 3× in this paper · explained in 4 episodes
• Interpretability — 3× in this paper · explained in 15 episodes
• Mixture of Experts (MoE) — 3× in this paper · explained in 5 episodes
• Mixture-of-Experts (MoE) — 3× in this paper · explained in 7 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Convolutional Neural Networks (CNNs) — 2× in this paper · explained in 2 episodes
• Data Augmentation — 2× in this paper · explained in 7 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• Edge Devices — 2× in this paper · explained in 2 episodes
• Ensemble Learning — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• Knowledge Distillation — 2× in this paper · explained in 11 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Adaptive Expert Routing — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 2 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 1× in this paper
• Global Average Pooling — 1× in this paper
• Hybrid Architectures — 1× in this paper · explained in 3 episodes
• Multi-Layer Perceptron — 1× in this paper
• Representation Learning — 1× in this paper · explained in 2 episodes
• Support Vector Machine — 1× in this paper
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Transformer Models — 1× in this paper · explained in 2 episodes
• Vision Transformer (ViT) — 1× in this paper · explained in 2 episodes

Sources

• Multi-objective hybrid knowledge distillation for efficient deep learning in smart agriculture
• MobileNetV2: Inverted Residuals and Linear Bottlenecks
• EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
• Deep Residual Learning for Image Recognition

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