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- Title
SP-ILC: Concurrent Single-Pixel Imaging, Object Location, and Classification by Deep Learning.
- Authors
Yang, Zhe; Bai, Yu-Ming; Sun, Li-Da; Huang, Ke-Xin; Liu, Jun; Ruan, Dong; Li, Jun-Lin
- Abstract
We propose a concurrent single-pixel imaging, object location, and classification scheme based on deep learning (SP-ILC). We used multitask learning, developed a new loss function, and created a dataset suitable for this project. The dataset consists of scenes that contain different numbers of possibly overlapping objects of various sizes. The results we obtained show that SP-ILC runs concurrent processes to locate objects in a scene with a high degree of precision in order to produce high quality single-pixel images of the objects, and to accurately classify objects, all with a low sampling rate. SP-ILC has potential for effective use in remote sensing, medical diagnosis and treatment, security, and autonomous vehicle control.
- Subjects
DEEP learning; DIAGNOSIS; PSEUDOPOTENTIAL method; REMOTE sensing; THERAPEUTICS; CLASSIFICATION
- Publication
Photonics, 2021, Vol 8, Issue 9, p400
- ISSN
2304-6732
- Publication type
Article
- DOI
10.3390/photonics8090400