کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
530767 | 869787 | 2014 | 10 صفحه PDF | دانلود رایگان |
• A synergistic combination of K-SVD and SRC Note.
• No extra parameter is introduced.
• More accurate recognition rate.
• Fewer inputs/assumptions.
The paper presents a supervised discriminative dictionary learning algorithm specially designed for classifying HEp-2 cell patterns. The proposed algorithm is an extension of the popular K-SVD algorithm: at the training phase, it takes into account the discriminative power of the dictionary atoms and reduces their intra-class reconstruction error during each update. Meanwhile, their inter-class reconstruction effect is also considered. Compared to the existing extension of K-SVD, the proposed algorithm is more robust to parameters and has better discriminative power for classifying HEp-2 cell patterns. Quantitative evaluation shows that the proposed algorithm outperforms general object classification algorithms significantly on standard HEp-2 cell patterns classifying benchmark1 and also achieves competitive performance on standard natural image classification benchmark.
Journal: Pattern Recognition - Volume 47, Issue 7, July 2014, Pages 2379–2388