Weight Prediction

Weight prediction research spans diverse applications, aiming to accurately estimate weight from various data sources, including images and videos, to improve healthcare, agriculture, and machine learning optimization. Current research focuses on leveraging deep learning, particularly convolutional neural networks (CNNs) and transformer architectures, often incorporating techniques like contrastive learning and mixed models to enhance prediction accuracy. These advancements are improving the precision of weight estimation in areas such as fetal birth weight prediction, monitoring livestock health, and optimizing deep learning model training, leading to more efficient and effective applications across multiple fields.