Test Image

Test image analysis encompasses diverse research areas focused on improving the reliability and robustness of image-based systems. Current efforts concentrate on developing methods for verifying image authenticity (e.g., watermarking for medical images), adapting models to handle variations in image distributions (e.g., using prompt-based test-time adaptation for medical segmentation), and detecting image manipulations (e.g., deepfake detection using multi-view and multi-scale networks). These advancements are crucial for ensuring the trustworthiness of image data across various applications, from medical diagnostics and remote sensing to combating the spread of misinformation.