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An Efficient and Light-weight Detector for Wine Bottle Defects
- Source :
- ICARCV
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- Detecting defects on the wine bottle surface is a challenging task due to these factors: (1) tiny defects on the surface, (2) visually similar defects with design patterns on bottles, (3) reflective (metallic) bottle surface, (4) real-time requirement. In this paper, we propose an efficient and light-weight detector for the defects. To this end, we adopt EfficientNet- B3 [1] as the backbone of the detector and YOLO [2] as the detection head. In addition, we use channel pruning approach [3] to obtain a more compact model. In the experiments, we obtain a score of 0.77 on the validation dataset, similar performance comparing to the two-stage methods[23]. The parameters of our detector are only 5. $8\mathrm{M}$ , which are about one tenth of the YOLO's [2]. The proposed detector achieves a good balance between speed and accuracy.
- Subjects :
- Wine bottle
Materials science
business.product_category
Channel (digital image)
business.industry
Detector
02 engineering and technology
010501 environmental sciences
Surface (topology)
01 natural sciences
Convolution
Optics
Kernel (image processing)
0202 electrical engineering, electronic engineering, information engineering
Bottle
020201 artificial intelligence & image processing
business
Pruning (morphology)
0105 earth and related environmental sciences
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV)
- Accession number :
- edsair.doi...........f3fba47b798485c1b3906a964f6796fc