Laser & Optoelectronics Progress, Volume. 55, Issue 11, 111507(2018)
Loop Closure Detection Algorithm Based On Multi-Level Convolutional Neural Network Features
Fig. 2. Sample images of Gardens Point dataset. (a) Day_left; (b) day_right; (c) night_right
Fig. 3. Visualization of similarity matrix for Gardens Point dataset. (a) pool3+pool5+fc1; (b) pool1; (c) pool3; (d) fc1
Fig. 6. Dynamic object detection results for YOLOv2. (a) Results of YOLOv2 method; (b) results of proposed method
Fig. 7. Flow of loop closure detection based on image dynamic interference semantic filter mechanism
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Zhenqiang Bao, Aihua Li, Zhigao Cui, Yanzhao Su, Yong Zheng. Loop Closure Detection Algorithm Based On Multi-Level Convolutional Neural Network Features[J]. Laser & Optoelectronics Progress, 2018, 55(11): 111507
Category: Machine Vision
Received: Apr. 21, 2018
Accepted: Jun. 6, 2018
Published Online: Aug. 14, 2019
The Author Email: Zhenqiang Bao (bzhenqiang@163.com)