Multi Band

Multi-band research encompasses diverse applications leveraging the advantages of utilizing multiple frequency bands or modalities simultaneously. Current efforts focus on improving the accuracy and efficiency of tasks like lesion segmentation in medical imaging (employing architectures such as nnU-Net and YOLOv8) and audio waveform reconstruction (using rectified flow models), often addressing challenges related to data scarcity, noise, and computational cost. These advancements have significant implications for improving diagnostic capabilities in medicine, enhancing audio processing technologies, and optimizing communication systems in challenging environments. The overarching goal is to develop robust and efficient algorithms that effectively integrate information across multiple bands for improved performance in various domains.