تقرير
Deep Unrolled Recovery in Sparse Biological Imaging
| العنوان: | Deep Unrolled Recovery in Sparse Biological Imaging |
|---|---|
| المؤلفون: | Sahel, Yair Ben, Bryan, John P., Cleary, Brian, Farhi, Samouil L., Eldar, Yonina C. |
| سنة النشر: | 2021 |
| المجموعة: | Computer Science Mathematics |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Computer Science - Information Theory, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Signal Processing |
| الوصف: | Deep algorithm unrolling has emerged as a powerful model-based approach to develop deep architectures that combine the interpretability of iterative algorithms with the performance gains of supervised deep learning, especially in cases of sparse optimization. This framework is well-suited to applications in biological imaging, where physics-based models exist to describe the measurement process and the information to be recovered is often highly structured. Here, we review the method of deep unrolling, and show how it improves source localization in several biological imaging settings. |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2109.14025 |
| رقم الأكسشن: | edsarx.2109.14025 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |