AN ATTENTION-BASED FUSION ARCHITECTURE FOR MULTIMODAL CROP DISEASE DETECTION AND ITS DEPLOYMENT ON EDGE DEVICES

The thesis presents a conceptual multimodal architecture that fuses image and sensor data through an attention mechanism for the early detection of crop diseases, together with its mathematical formulation, dataset construction procedure, evaluation criteria, and the prospects of deploying the model on resource-constrained edge devices.