Molecular Image

Molecular image analysis focuses on extracting meaningful information from images of molecules, enabling automated chemical structure recognition and property prediction. Current research emphasizes deep learning models, particularly graph neural networks and convolutional neural networks (often combined), to process these images and translate them into machine-readable formats like SMILES strings or graph representations. This field is crucial for accelerating drug discovery, materials science, and other domains by automating tasks previously reliant on time-consuming manual analysis, improving efficiency and potentially leading to new discoveries.