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This paper introduces a web image search reranking approach that explores multiple modalities in a graph-based learning scheme. Different from the conventional methods that usually adopt a single modality or integrate multiple modalities into a long feature vector, our approach can effectively integrate the learning of relevance scores, weights of(More)
Hedgehogs (Hhs) are key signaling regulators of stem cell maintenance and tissue patterning in embryos, and activating mutations in the pathway that increase Gli transcriptional activity are causal in a diversity of cancers. Here, we report that phosphoinositide 3-kinase (PI3-kinase)-dependent Akt activation is essential for Sonic Hedgehog (Shh) signaling(More)
Hedgehog (HH) signaling regulates a diversity of processes involved in developmental patterning, stem cell growth and maintenance, and cancer etiology. Despite its biological importance, the HH signal transduction pathway remains largely mysterious. Our past understanding of the HH pathway signaling components and mechanisms came from groundbreaking genetic(More)
—Weakly-supervised image segmentation is a challenging problem with multidisciplinary applications in multimedia content analysis and beyond. It aims to segment an image by lever-aging its image-level semantics (i.e., tags). This paper presents a weakly-supervised image segmentation algorithm that learns the distribution of spatially structural superpixel(More)
Binary hashing has been widely used for efficient similarity search due to its query and storage efficiency. In most existing binary hashing methods, the high-dimensional data are embedded into Hamming space and the distance or similarity of two points are approximated by the Hamming distance between their binary codes. The Hamming distance calculation is(More)
Researchers have proposed various machine learning algorithms for traffic sign recognition, which is a supervised multicategory classification problem with unbalanced class frequencies and various appearances. We present a novel graph embedding algorithm that strikes a balance between local manifold structures and global discriminative information. A novel(More)
Mice have proved to be a powerful model organism for understanding obesity in humans. Single gene mutants and genetically modified mice have been used to identify obesity genes, and the discovery of loci for polygenic forms of obesity in the mouse is an important next step. To pursue this goal, the inbred mouse strains 129P3/J (129) and C57BL/6ByJ (B6),(More)
The interplay between sexes is a prerequisite for female growth, reproductive maturation, and egg production, and the basis of schistosome pathopoiesis and propagation. The tegument is in direct contact with the host environment and its surface membranes are particularly crucial for schistosome survival in the definitive host. In this study, a(More)
3D object retrieval has attracted extensive research efforts and become an important task in recent years. It is noted that how to measure the relevance between 3D objects is still a difficult issue. Most of the existing methods employ just the model-based or view-based approaches, which may lead to incomplete information for 3D object representation. In(More)