Oil Palm Tree Detection for Anomaly Identification

This dataset supports an advanced artificial vision system for detecting anomalies in oil palm (Elaeis guineensis) crops. It consists of RGB captured using a DJI Phantom 4 Multispectral UAV. The dataset is labeled into two main classes: 'PalmSan' (healthy palms) and 'PalmAnom' (anomalous palms). It was used to train and validate a Faster R-CNN with ResNet-50 FPN model, fine-tuned in PyTorch. The dataset plays a crucial role in high-accuracy classification for automated disease detection and stress assessment, contributing to scalable and sustainable precision agriculture solutions.