CNN refinement based object recognition through optimized segmentation

As one classic technique, object recognition could identify objects in an image effectively and it has been improved by deep learning model significantly. However, in the process of object recognition, complicated background could have negative on the feature extraction which directly reduces the quality of object recognition. Although some methods have targeted for the drawbacks, the quality of feature extraction is still not realistic. Aiming at the problem above, we proposed one CNN refinement based object recognition through optimized segmentation method which could improve the quality of object recognition. On the one hand, optimized segmentation method could contribute to the process of feature extraction. On the other hand, CNN refinement method could contribute to achieve the final object recognition. At last, the database with a large number of images was built. Based on it, adequate experiments verify our model's effectiveness and robustness. (C) 2017 Elsevier GmbH. All rights reserved.