کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6865545 | 679059 | 2015 | 22 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Image classification based on low-rank matrix recovery and Naive Bayes collaborative representation
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Image classification based on low-rank matrix recovery and Naive Bayes collaborative representation Image classification based on low-rank matrix recovery and Naive Bayes collaborative representation](/preview/png/6865545.png)
چکیده انگلیسی
Most image classification methods require an expensive learning/training phase to gain high performances. But they frequently encounter problems such as overfitting of parameters and scarcity of training data. In this paper, we present a novel learning-free image classification algorithm under the framework of Naive-Bayes Nearest-Neighbor (NBNN) and collaborative representation, where non-negative sparse coding, low-rank matrix recovery and collaborative representation are jointly employed to obtain more robust and discriminative representation. First, instead of using general sparse coding, non-negative sparse coding combined with max pooling is introduced to further reduce information loss. Second, we use the low-rank matrix recovery technique to decompose the training data of the same class into a discriminative low-rank matrix, in which more structurally correlated information is preserved. As for testing images, a low-rank projection matrix is also learned to remove possible image corruptions. Finally, the classification process is implemented by simply comparing the responses over the different bases. Experimental results on several image datasets demonstrate the effectiveness of our method.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 169, 2 December 2015, Pages 110-118
Journal: Neurocomputing - Volume 169, 2 December 2015, Pages 110-118
نویسندگان
Xu Zhang, Shijie Hao, Chenyang Xu, Xueming Qian, Meng Wang, Jianguo Jiang,