CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
Brain slices microscopic detection using simplified SSD with Cycle-GAN data augmentation
Weizhou Liu1,2; Long Cheng1,2; Deyuan Meng3
2018
Conference NameThe 25th International Conference on Neural Information Processing
Conference Date13-16 Dec. 2018
Conference PlaceSiem Reap
CountryCambodia
Abstract

Orderly automatic collection of brain slices on the silicon substrate is critical for understanding the working principle of the whole-brain neural network. Accurate and real-time brain slices detection with microscopic CCD is crucial for automatic collection of brain slices. To solve this task, an efficient simplified SSD detection model with Cycle-GAN data augmentation is presented in this paper. The proposed simplified SSD streamlines the detection network of the original SSD architecture, leading to a more rapid detection. Moreover, the proposed Cycle-GAN data augmentation method overcomes the limitation of training images. To verify the effectiveness of the proposed method, experiments are conducted with a self-made brain slices dataset. The experiment results suggest that, the proposed method has a good performance of rapidly detecting brain slices with only a small training dataset.

Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/23116
Collection复杂系统管理与控制国家重点实验室_先进机器人
复杂系统管理与控制国家重点实验室
Affiliation1.State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
3.School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Weizhou Liu,Long Cheng,Deyuan Meng. Brain slices microscopic detection using simplified SSD with Cycle-GAN data augmentation[C],2018.
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