@article{Koizumi_Hiraki_Inaba_2018, title={Skyline Computation for Low-Latency Image-Activated Cell Identification}, volume={32}, url={https://ojs.aaai.org/index.php/AAAI/article/view/12134}, DOI={10.1609/aaai.v32i1.12134}, abstractNote={ <p> High-throughput label-free single cell screening technology has been studied for noninvasive analysis of various kinds of cells. We tackle the cell identification task in the cell sorting system as a continuous skyline computation. Skyline Computation is a method for extracting interesting entries from a large population with multiple attributes. Jointed rooted-tree (JR-tree) is continuous skyline computation algorithm that manages entries using a rooted-tree structure. JR-tree delays extend the tree to deeper levels to accelerate tree construction and traversal. In this study, we proposed the JR-tree-based parallel skyline computation accelerator. We implemented it on a field-programmable gate array (FPGA). We evaluated our proposed software and hardware algorithms against an existing software algorithm using synthetic and real-world datasets. </p> }, number={1}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Koizumi, Kenichi and Hiraki, Kei and Inaba, Mary}, year={2018}, month={Apr.} }