Stroke Level

Stroke-level analysis focuses on understanding and manipulating individual strokes within images, particularly in the context of scene sketching, character recognition, and text editing. Current research employs various deep learning architectures, including transformers and diffusion probabilistic models, often incorporating novel loss functions and stroke encoding methods to improve accuracy and efficiency. This detailed level of analysis is proving crucial for advancing applications such as assistive drawing, semantic segmentation of sketches, and improved medical image analysis for stroke diagnosis and treatment, ultimately leading to more effective and nuanced image processing techniques.