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Visualizing Deep Neural Networks with Interaction of Super-pixels
- Source :
- CIKM
- Publication Year :
- 2017
- Publisher :
- ACM, 2017.
-
Abstract
- An effective way to visualize the prediction of deep neural networks on an image is to decompose the prediction into the contribution of units (pixels or patches). In the existing works, these units are largely considered independently, thus limiting the performance of visualization. In this paper, we propose a new predication visualization method that uses super-pixel as a contribution unit. Moreover, our method takes into consideration of the interaction of adjacent super-pixels. We implement our technique and evaluate its performance with various images. Our results show its excellent performance.
- Subjects :
- Contextual image classification
Pixel
Computer science
business.industry
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Pattern recognition
02 engineering and technology
Visualization
Image (mathematics)
Computer Science::Computer Vision and Pattern Recognition
020204 information systems
0202 electrical engineering, electronic engineering, information engineering
Deep neural networks
020201 artificial intelligence & image processing
Artificial intelligence
business
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Proceedings of the 2017 ACM on Conference on Information and Knowledge Management
- Accession number :
- edsair.doi...........26cba81fdc2ed6e265ed6bb81093e5f8