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Title: Fast Neural Cell Detection Using Light-Weight SSD Neural Network
Identifying the lineage path of neural cells is critical for understanding the development of brain. Accurate neural cell detection is a crucial step to obtain reliable delineation of cell lineage. To solve this task, in this paper we present an efficient neural cell detection method based on SSD (single shot multibox detector) neural network model. Our method adapts the original SSD architecture and removes the un- necessary blocks, leading to a light-weight model. More- over, we formulate the cell detection as a binary regression problem, which makes our model much simpler. Experimen- tal results demonstrate that, with only a small training set, our method is able to accurately capture the neural cells under severe shape deformation in a fast way.
Authors:
; ; ;
Award ID(s):
1747778
Publication Date:
NSF-PAR ID:
10105318
Journal Name:
CVPR Workshop
Sponsoring Org:
National Science Foundation
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