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Segmenting Unknown 3D Objects from Real Depth Images using Mask R-CNN Trained on Synthetic Data.

, , , , , , and . ICRA, page 7283-7290. IEEE, (2019)

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Introduction of customized inserts for streamlined assembly and optimization of BioBrick synthetic genetic circuits., , , , , , and . Journal of biological engineering, (Dec 20, 2010)Do I matter?: the impact of individual differences on training process., , and . CPR, page 112-120. ACM, (2010)Locality principle revisited: A probability-based quantitative approach., , , and . J. Parallel Distributed Comput., 73 (7): 1011-1027 (2013)Understanding GPU errors on large-scale HPC systems and the implications for system design and operation., , , , , , , , , and 2 other author(s). HPCA, page 331-342. IEEE Computer Society, (2015)Segmenting Unknown 3D Objects from Real Depth Images using Mask R-CNN Trained on Synthetic Data., , , , , , and . ICRA, page 7283-7290. IEEE, (2019)Cognitive Mapping and Planning for Visual Navigation., , , , and . CVPR, page 7272-7281. IEEE Computer Society, (2017)Spatial Locality-Aware Cache Partitioning for Effective Cache Sharing., and . ICPP, page 150-159. IEEE Computer Society, (2015)Effective Running of End-to-End HPC Workflows on Emerging Heterogeneous Architectures., , , , and . CLUSTER, page 344-348. IEEE Computer Society, (2017)Locality Principle Revisited: A Probability-Based Quantitative Approach., , , and . IPDPS, page 995-1009. IEEE Computer Society, (2012)Improving large-scale storage system performance via topology-aware and balanced data placement., , , , and . ICPADS, page 656-663. IEEE Computer Society, (2014)