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A rapid, sensitive and quantitative biomarker detection platform is of great importance to the small clinic or point-of-care (POC) diagnosis. In this work, we realize that an automated diagnostic platform mainly includes two components: (1) an instrument that can complete all steps of the chemiluminescence immunoassay automatically and (2) an integrated microfluidic chip which is disposable and harmless...
In the hashing approaches with multi-bit quantization, each projected dimension is divided into multiple regions indexed with multiple bits to preserve the neighborhood structure of the data. However, the query is processed in binary, and the distances between the adjacent regions are usually assumed to be equal, resulting in the accuracy loss of the computed distance between the data and the query...
Usually, most of hashing methods for information retrieval have a two-step procedure, embedding the data into a low-dimensional intermediate space and then quantizing them into binary codes. In the hyperplane-based hashing methods, the distance between the data in the intermediate space can replace the Hamming distance to improve the retrieval accuracy. In this paper, a novel asymmetric distance for...
Metric learning is an effective method for person re-identification. It utilizes latent factors to find a suitable space for measuring distances. In general, a small number of factors are not powerful enough to match the pedestrians while a large number of factors cause high computational cost. In this paper, to balance this trade-off, a novel diversity regularized distance metric learning method...
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