|Table of Contents|

A Circular Object Detector with Anti-Noise Performance(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2021年04期
Page:
85-93
Research Field:
·计算机科学与技术·
Publishing date:

Info

Title:
A Circular Object Detector with Anti-Noise Performance
Author(s):
Cai Zhongsheng; Chen Fei; Zeng Xunxun
College of Mathematics and Computer Science,Fuzhou University,Fuzhou 350108,China
Keywords:
noisy image; object detection; IOU loss; shape feature; prior information
PACS:
TP751
DOI:
10.3969/j.issn.1001-4616.2021.04.011
Abstract:
At present,many of the target detection models will suffer from precision degradation in noisy environment. In order to improve the accuracy of target detection model in noisy environment,two methods are proposed. Firstly,an anti-noise feature extraction module based on residual structure is proposed to support the subsequent network modules. Secondly,the anchor frame design and loss function design of the model are improved by using the prior information of the target. The shape of the anchor frame is designed according to the shape prior information of the target. The IOU loss function is taken as the Bbox loss function of the model,in which the IOU loss term and the minimum closure area are calculated according to the prior information of the target shape. The experimental data sets were blood cell data sets and inferior parathyroid gland data sets,and the benchmark control models were Yolov3 and RetinaNet,which can also be transplanted to other detection models. In the blood cell dataset environment,the accuracy of Yolov3 is 62.7,which is improved to 75.7,which is a great improvement. In the inferior parathyroid gland data set,there was also an improvement.

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Last Update: 2021-12-15