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Empirically, we find that, despite the class-specific features owned by the objects appearing in the images, the objects from different categories usually share some common patterns, which do not contribute to the discrimination of them. Concentrating on this observation and under the general dictionary learning (DL) framework, we propose a novel method to(More)
A Aesthetics & Attribute Database (AADB) Fusing Attributes and Content for Aesthetics Ranking Demo, code and model can be download through project webpage http://www.ics.uci.edu/~skong2/aesthetics.html References: [8] He, K., Zhang, X., Ren, S., Sun, J., ECCV, 2014 [15] Lu, X., Lin, Z., Jin, H., Yang, J., Wang, J., IEEE Trans. on Multimedia, 2015 [16] Lu,(More)
BACKGROUND Human embryonic stem cell (hESC) lines derived from poor quality embryos usually have either normal or abnormal karyotypes. However, it is still unclear whether their biological characteristics are similar. METHODS Seven new hESC lines were established using discarded embryos. Five cell lines had normal karyotype, one was with an unbalanced(More)
This paper introduces a simple but highly efficient ensemble for robust texture classification, which can effectively deal with translation, scale and changes of significant viewpoint problems. The proposed method first inherits the spirit of spatial pyramid matching model (SPM), which is popular for encoding spatial distribution of local features, but in a(More)
We now know that mid-level features can greatly enhance the performance of image learning, but how to automatically learn the image features efficiently and in an unsupervised manner is still an open question. In this paper, we present a very efficient mid-level feature learning approach (MidFea), which only involves simple operations such as k-means(More)
Previous researches have demonstrated that the framework of dictionary learning with sparse coding, in which signals are decomposed as linear combinations of a few atoms of a learned dictionary, is well adept to reconstruction issues. This framework has also been used for discrimination tasks such as image classification. To achieve better performances of(More)
BACKGROUND Achondroplasia is a well-defined and common bone dysplasia. Genotype- and phenotype-level correlations have been found between the clinical symptoms of achondroplasia and achondroplasia-specific FGFR3 mutations. RESULT A 2-year-old boy with clinical features consistent with achondroplasia and Silver-Russell syndrome-like symptoms was found to(More)
To tackle the problem of saliency detection in images, we propose to learn adaptive mid-level features to represent image local information, and present an efficient way to calculate multi-scale and multi-level saliency maps. With the simple k-means algorithm, we learn adaptive low-level filters to convolve the image to produce response maps as the(More)