Two Stage Approach

A two-stage approach is a prevalent strategy in various fields leveraging the power of modularity and specialization to solve complex problems. Current research focuses on applying this approach with diverse model architectures, including deep learning models (like transformers and LSTMs), and optimization techniques to improve accuracy, efficiency, and robustness in tasks ranging from image generation and processing to natural language processing and medical diagnosis. This methodology's significance lies in its ability to decompose intricate challenges into manageable sub-problems, leading to improved performance and interpretability compared to single-stage methods across a wide range of applications.