METER Based Correction

METER-based approaches encompass a range of techniques leveraging machine learning, particularly deep learning models like vision transformers, to address diverse challenges involving meter reading and data analysis. Current research focuses on improving the accuracy and efficiency of these methods, particularly for applications with limited computational resources or noisy data, through novel architectures and loss functions. These advancements have significant implications for various fields, including autonomous systems, anomaly detection, and automated infrastructure inspection, enabling more efficient data acquisition and analysis in diverse real-world scenarios.