Label-free Anomaly Detection in Aerial Agricultural Images with Masked Image Modeling

arXiv:2404.08931v1 Announce Type: cross
Abstract: Detecting various types of stresses (nutritional, water, nitrogen, etc.) in agricultural fields is critical for farmers to ensure maximum productivity. However, stresses show up in different shapes and sizes across different crop types and varieties. Hence, this is posed as an anomaly detection task in agricultural images. Accurate anomaly detection in agricultural UAV images is vital for early identification of field irregularities. Traditional supervised learning faces challenges in adapting to diverse anomalies, necessitating extensive annotated …

abstract aerial anomaly anomaly detection arxiv cs.ai cs.cv cs.lg detection etc farmers fields free however image images modeling productivity show type types water