Agricultural Image

Agricultural image analysis focuses on using computer vision techniques to improve efficiency and decision-making in farming. Current research emphasizes leveraging deep learning models, including convolutional neural networks (CNNs) and transformers, often enhanced by techniques like data augmentation (including GANs) and class balancing to address issues such as data scarcity and class imbalance in agricultural datasets. This field is crucial for advancing precision agriculture, enabling automated tasks like crop monitoring, yield prediction, and robotic harvesting, ultimately contributing to increased food production and sustainability.