Using Computer Vision Technologies to Make the Virtual Visible

Mobile Life CentreMobile 2.

Recognizing Art Pieces in Subway using Computer Vision

We present a mobile application that automatically recognizes art pieces in the subway. Users can take a photo of an art piece with their mobile phones, and by using image recognition our system retrieves information about that particular art piece. By combining the location with image data, we can delimit the dataset of photos of art pieces to speed up the image recognition. The image recognition is based on feature detection using SURF, and by matching feature points using kd-trees for storing the interest points of the training data. We propose a method for selecting good training images when creating the database. In addition, we also cluster the training interest points by the k-means algorithm, which reduces the space of the kd-tree and increase the matching speed. We demonstrate the effectiveness of our approach with an application that allows users to enjoy the art pieces at different subway stations through image recognition

Recognizing Art Pieces in Subway using Computer Vision

We present a mobile application that automatically recognizes art pieces in the subway. Users can take a photo of an art piece with their mobile phones, and by using image recognition our system retrieves information about that particular art piece. By combining the location with image data, we can delimit the dataset of photos of art pieces to speed up the image recognition. The image recognition is based on feature detection using SURF, and by matching feature points using kd-trees for storing the interest points of the training data. We propose a method for selecting good training images when creating the database. In addition, we also cluster the training interest points by the k-means algorithm, which reduces the space of the kd-tree and increase the matching speed. We demonstrate the effectiveness of our approach with an application that allows users to enjoy the art pieces at different subway stations through image recognition

Recognizing Art Pieces in Subway using Computer Vision

We present a mobile application that automatically recognizes art pieces in the subway. Users can take a photo of an art piece with their mobile phones, and by using image recognition our system retrieves information about that particular art piece. By combining the location with image data, we can delimit the dataset of photos of art pieces to speed up the image recognition. The image recognition is based on feature detection using SURF, and by matching feature points using kd-trees for storing the interest points of the training data. We propose a method for selecting good training images when creating the database. In addition, we also cluster the training interest points by the k-means algorithm, which reduces the space of the kd-tree and increase the matching speed. We demonstrate the effectiveness of our approach with an application that allows users to enjoy the art pieces at different subway stations through image recognition

Growth Hormone-Releasing Hormone in Lung Physiology and Pulmonary Disease

Growth hormone-releasing hormone (GHRH) is secreted primarily from the hypothalamus, but other tissues, including the lungs, produce it locally. GHRH stimulates the release and secretion of growth hormone (GH) by the pituitary and regulates the production of GH and hepatic insulin-like growth factor-1 (IGF-1). Pituitary-type GHRH-receptors (GHRH-R) are expressed in human lungs, indicating that GHRH or GH could participate in lung development, growth, and repair. GHRH-R antagonists (i.e., synthetic peptides), which we have tested in various models, exert growth-inhibitory effects in lung cancer cells in vitro and in vivo in addition to having anti-inflammatory, anti-oxidative, and pro-apoptotic effects. One antagonist of the GHRH-R used in recent studies reviewed here, MIA-602, lessens both inflammation and fibrosis in a mouse model of bleomycin lung injury. GHRH and its peptide agonists regulate the proliferation of fibroblasts through the modulation of extracellular signal-regulated kinase (ERK) and Akt pathways. In addition to downregulating GH and IGF-1, GHRH-R antagonist MIA-602 inhibits signaling pathways relevant to inflammation, including p21-activated kinase 1-signal transducer and activator of transcription 3/nuclear factor-kappa B (PAK1-STAT3/NF-κB and ERK). MIA-602 induces fibroblast apoptosis in a dose-dependent manner, which is an effect that is likely important in antifibrotic actions. Taken together, the novel data reviewed here show that GHRH is an important peptide that participates in lung homeostasis, inflammation, wound healing, and cancer; and GHRH-R antagonists may have therapeutic potential in lung diseases

Identification of ENO1 as a prognostic biomarker and molecular target among ENOs in bladder cancer

Abstract Background Enolase is an essential enzyme in the process of glycolysis and has been implicated in cancer progression. Though dysregulation of ENOs has been reported in multiple cancers, their prognostic value and specific role in bladder cancer (BLCA) remain unclear. Methods Multiple databases were employed to examine the expression of ENOs in BLCA. The expression of ENO1 was also validated in BLCA cell lines and tissue samples by western blotting and immunohistochemistry. Kaplan–Meier analysis, ROC curve, univariate and multivariate Cox regression were performed to evaluate the predictive capability of the ENO1. Gene ontology (GO) and Gene Set Enrichment Analyses (GSEA) analysis were employed to perform the biological processes enrichment. Function experiments were performed to explore the biological role of ENO1 in BLCA. The correlation of ENO1 with immune cell infiltration was explored by CIBERSORT. Results By analyzing three ENO isoforms in multiple databases, we identified that ENO1 was the only significantly upregulated gene in BLCA. High expression level of ENO1 was further confirmed in BLCA tissue samples. Aberrant ENO1 overexpression was associated with clinicopathological characteristics and unfavorable prognosis. Functional studies demonstrated that ENO1 depletion inhibited cancer cell aggressiveness. Furthermore, the expression level of ENO1 was correlated with the infiltration levels of immune cells and immune-related functions. Conclusions Taken together, our results indicated that ENO1 might serve as a promising prognostic biomarker for prognosticating prognosis associated with the tumor immune microenvironment, suggesting that ENO1 could be a potential immune-related target against BLCA

Synthesis and structure-activity studies on novel analogs of human growth hormone releasing hormone (GHRH) with enhanced inhibitory activities on tumor growth

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